Text Generation
Transformers
Safetensors
qwen2
Generated from Trainer
X-R1
conversational
text-generation-inference
Instructions to use watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero") model = AutoModelForCausalLM.from_pretrained("watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero
- SGLang
How to use watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero with Docker Model Runner:
docker model run hf.co/watermelonhjg/Qwen2.5-3B-Instruct-EN-Zero
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- README.md +67 -0
- added_tokens.json +24 -0
- all_results.json +8 -0
- config.json +29 -0
- generation_config.json +14 -0
- merges.txt +0 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +441 -0
- special_tokens_map.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +209 -0
- train_results.json +8 -0
- trainer_state.json +2479 -0
- training_args.bin +3 -0
- vocab.json +0 -0
- wandb_run_id.txt +1 -0
.gitattributes
CHANGED
|
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 34 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 35 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 36 |
+
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
|
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen2.5-3B-Instruct
|
| 3 |
+
datasets: xiaodongguaAIGC/X-R1-7500
|
| 4 |
+
library_name: transformers
|
| 5 |
+
tags:
|
| 6 |
+
- generated_from_trainer
|
| 7 |
+
- X-R1
|
| 8 |
+
licence: license
|
| 9 |
+
---
|
| 10 |
+
|
| 11 |
+
# Model Card for None
|
| 12 |
+
|
| 13 |
+
This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the [xiaodongguaAIGC/X-R1-7500](https://huggingface.co/datasets/xiaodongguaAIGC/X-R1-7500) dataset.
|
| 14 |
+
It has been trained using [TRL](https://github.com/huggingface/trl).
|
| 15 |
+
|
| 16 |
+
## Quick start
|
| 17 |
+
|
| 18 |
+
```python
|
| 19 |
+
from transformers import pipeline
|
| 20 |
+
|
| 21 |
+
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
|
| 22 |
+
generator = pipeline("text-generation", model="None", device="cuda")
|
| 23 |
+
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
|
| 24 |
+
print(output["generated_text"])
|
| 25 |
+
```
|
| 26 |
+
|
| 27 |
+
## Training procedure
|
| 28 |
+
|
| 29 |
+
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/watermelonhjg/huggingface/runs/d1x61l64)
|
| 30 |
+
|
| 31 |
+
|
| 32 |
+
This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
|
| 33 |
+
|
| 34 |
+
### Framework versions
|
| 35 |
+
|
| 36 |
+
- TRL: 0.14.0
|
| 37 |
+
- Transformers: 4.48.3
|
| 38 |
+
- Pytorch: 2.5.1
|
| 39 |
+
- Datasets: 3.2.0
|
| 40 |
+
- Tokenizers: 0.21.0
|
| 41 |
+
|
| 42 |
+
## Citations
|
| 43 |
+
|
| 44 |
+
Cite GRPO as:
|
| 45 |
+
|
| 46 |
+
```bibtex
|
| 47 |
+
@article{zhihong2024deepseekmath,
|
| 48 |
+
title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
|
| 49 |
+
author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
|
| 50 |
+
year = 2024,
|
| 51 |
+
eprint = {arXiv:2402.03300},
|
| 52 |
+
}
|
| 53 |
+
|
| 54 |
+
```
|
| 55 |
+
|
| 56 |
+
Cite TRL as:
|
| 57 |
+
|
| 58 |
+
```bibtex
|
| 59 |
+
@misc{vonwerra2022trl,
|
| 60 |
+
title = {{TRL: Transformer Reinforcement Learning}},
|
| 61 |
+
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
|
| 62 |
+
year = 2020,
|
| 63 |
+
journal = {GitHub repository},
|
| 64 |
+
publisher = {GitHub},
|
| 65 |
+
howpublished = {\url{https://github.com/huggingface/trl}}
|
| 66 |
+
}
|
| 67 |
+
```
|
added_tokens.json
ADDED
|
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"</tool_call>": 151658,
|
| 3 |
+
"<tool_call>": 151657,
|
| 4 |
+
"<|box_end|>": 151649,
|
| 5 |
+
"<|box_start|>": 151648,
|
| 6 |
+
"<|endoftext|>": 151643,
|
| 7 |
+
"<|file_sep|>": 151664,
|
| 8 |
+
"<|fim_middle|>": 151660,
|
| 9 |
+
"<|fim_pad|>": 151662,
|
| 10 |
+
"<|fim_prefix|>": 151659,
|
| 11 |
+
"<|fim_suffix|>": 151661,
|
| 12 |
+
"<|im_end|>": 151645,
|
| 13 |
+
"<|im_start|>": 151644,
|
| 14 |
+
"<|image_pad|>": 151655,
|
| 15 |
+
"<|object_ref_end|>": 151647,
|
| 16 |
+
"<|object_ref_start|>": 151646,
|
| 17 |
+
"<|quad_end|>": 151651,
|
| 18 |
+
"<|quad_start|>": 151650,
|
| 19 |
+
"<|repo_name|>": 151663,
|
| 20 |
+
"<|video_pad|>": 151656,
|
| 21 |
+
"<|vision_end|>": 151653,
|
| 22 |
+
"<|vision_pad|>": 151654,
|
| 23 |
+
"<|vision_start|>": 151652
|
| 24 |
+
}
|
all_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"total_flos": 0.0,
|
| 3 |
+
"train_loss": 0.11509215348958969,
|
| 4 |
+
"train_runtime": 61764.0604,
|
| 5 |
+
"train_samples": 7500,
|
| 6 |
+
"train_samples_per_second": 0.364,
|
| 7 |
+
"train_steps_per_second": 0.03
|
| 8 |
+
}
|
config.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "Qwen/Qwen2.5-3B-Instruct",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"Qwen2ForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"bos_token_id": 151643,
|
| 8 |
+
"eos_token_id": 151645,
|
| 9 |
+
"hidden_act": "silu",
|
| 10 |
+
"hidden_size": 2048,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 11008,
|
| 13 |
+
"max_position_embeddings": 32768,
|
| 14 |
+
"max_window_layers": 70,
|
| 15 |
+
"model_type": "qwen2",
|
| 16 |
+
"num_attention_heads": 16,
|
| 17 |
+
"num_hidden_layers": 36,
|
| 18 |
+
"num_key_value_heads": 2,
|
| 19 |
+
"rms_norm_eps": 1e-06,
|
| 20 |
+
"rope_scaling": null,
|
| 21 |
+
"rope_theta": 1000000.0,
|
| 22 |
+
"sliding_window": null,
|
| 23 |
+
"tie_word_embeddings": true,
|
| 24 |
+
"torch_dtype": "bfloat16",
|
| 25 |
+
"transformers_version": "4.48.3",
|
| 26 |
+
"use_cache": true,
|
| 27 |
+
"use_sliding_window": false,
|
| 28 |
+
"vocab_size": 151936
|
| 29 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 151643,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
151645,
|
| 6 |
+
151643
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 151643,
|
| 9 |
+
"repetition_penalty": 1.05,
|
| 10 |
+
"temperature": 0.7,
|
| 11 |
+
"top_k": 20,
|
| 12 |
+
"top_p": 0.8,
|
| 13 |
+
"transformers_version": "4.48.3"
|
| 14 |
+
}
|
merges.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
model-00001-of-00002.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c594376edf3af25fd0c0a7cbdca4cf2ecce6fd0629078fbda779da00f03edb23
|
| 3 |
+
size 4957560304
|
model-00002-of-00002.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:fb69250e2e29015502e2bf7e79f8178bd8977ac75612431c60cc8cf69fdb5ce7
|
| 3 |
+
size 1214366696
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,441 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 6171877376
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
+
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
| 7 |
+
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 8 |
+
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 9 |
+
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 10 |
+
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 11 |
+
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 12 |
+
"model.layers.0.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 13 |
+
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 14 |
+
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 15 |
+
"model.layers.0.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 16 |
+
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 17 |
+
"model.layers.0.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 18 |
+
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 19 |
+
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 20 |
+
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 21 |
+
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 22 |
+
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 23 |
+
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 24 |
+
"model.layers.1.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 25 |
+
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 26 |
+
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 27 |
+
"model.layers.1.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 28 |
+
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 29 |
+
"model.layers.1.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 30 |
+
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 31 |
+
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 32 |
+
"model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 33 |
+
"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 34 |
+
"model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 35 |
+
"model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 36 |
+
"model.layers.10.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 37 |
+
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 38 |
+
"model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 39 |
+
"model.layers.10.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 40 |
+
"model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 41 |
+
"model.layers.10.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 42 |
+
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 43 |
+
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 44 |
+
"model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 45 |
+
"model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 46 |
+
"model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 47 |
+
"model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 48 |
+
"model.layers.11.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 49 |
+
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 50 |
+
"model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 51 |
+
"model.layers.11.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 52 |
+
"model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 53 |
+
"model.layers.11.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 54 |
+
"model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 55 |
+
"model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 56 |
+
"model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 57 |
+
"model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 58 |
+
"model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 59 |
+
"model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 60 |
+
"model.layers.12.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 61 |
+
"model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 62 |
+
"model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 63 |
+
"model.layers.12.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 64 |
+
"model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 65 |
+
"model.layers.12.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 66 |
+
"model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 67 |
+
"model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 68 |
+
"model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 69 |
+
"model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 70 |
+
"model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 71 |
+
"model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 72 |
+
"model.layers.13.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 73 |
+
"model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 74 |
+
"model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 75 |
+
"model.layers.13.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 76 |
+
"model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 77 |
+
"model.layers.13.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 78 |
+
"model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 79 |
+
"model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 80 |
+
"model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 81 |
+
"model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 82 |
+
"model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 83 |
+
"model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 84 |
+
"model.layers.14.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 85 |
+
"model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 86 |
+
"model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 87 |
+
"model.layers.14.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 88 |
+
"model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 89 |
+
"model.layers.14.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 90 |
+
"model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 91 |
+
"model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 92 |
+
"model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 93 |
+
"model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 94 |
+
"model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 95 |
+
"model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 96 |
+
"model.layers.15.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 97 |
+
"model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 98 |
+
"model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 99 |
+
"model.layers.15.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 100 |
+
"model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 101 |
+
"model.layers.15.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 102 |
+
"model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 103 |
+
"model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 104 |
+
"model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 105 |
+
"model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 106 |
+
"model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 107 |
+
"model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 108 |
+
"model.layers.16.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 109 |
+
"model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 110 |
+
"model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 111 |
+
"model.layers.16.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 112 |
+
"model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 113 |
+
"model.layers.16.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 114 |
+
"model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 115 |
+
"model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 116 |
+
"model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 117 |
+
"model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 118 |
+
"model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 119 |
+
"model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 120 |
+
"model.layers.17.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 121 |
+
"model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 122 |
+
"model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 123 |
+
"model.layers.17.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 124 |
+
"model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 125 |
+
"model.layers.17.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 126 |
+
"model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 127 |
+
"model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 128 |
+
"model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 129 |
+
"model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 130 |
+
"model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 131 |
+
"model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 132 |
+
"model.layers.18.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 133 |
+
"model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 134 |
+
"model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 135 |
+
"model.layers.18.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 136 |
+
"model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 137 |
+
"model.layers.18.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 138 |
+
"model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 139 |
+
"model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 140 |
+
"model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 141 |
+
"model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 142 |
+
"model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 143 |
+
"model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 144 |
+
"model.layers.19.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 145 |
+
"model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 146 |
+
"model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 147 |
+
"model.layers.19.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 148 |
+
"model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 149 |
+
"model.layers.19.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 150 |
+
"model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 151 |
+
"model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 152 |
+
"model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 153 |
+
"model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 154 |
+
"model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 155 |
+
"model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 156 |
+
"model.layers.2.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 157 |
+
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 158 |
+
"model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 159 |
+
"model.layers.2.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 160 |
+
"model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 161 |
+
"model.layers.2.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 162 |
+
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 163 |
+
"model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 164 |
+
"model.layers.20.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 165 |
+
"model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 166 |
+
"model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 167 |
+
"model.layers.20.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 168 |
+
"model.layers.20.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 169 |
+
"model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 170 |
+
"model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 171 |
+
"model.layers.20.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 172 |
+
"model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 173 |
+
"model.layers.20.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 174 |
+
"model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 175 |
+
"model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 176 |
+
"model.layers.21.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 177 |
+
"model.layers.21.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 178 |
+
"model.layers.21.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 179 |
+
"model.layers.21.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 180 |
+
"model.layers.21.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 181 |
+
"model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 182 |
+
"model.layers.21.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 183 |
+
"model.layers.21.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 184 |
+
"model.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 185 |
+
"model.layers.21.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 186 |
+
"model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 187 |
+
"model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 188 |
+
"model.layers.22.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 189 |
+
"model.layers.22.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 190 |
+
"model.layers.22.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 191 |
+
"model.layers.22.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 192 |
+
"model.layers.22.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 193 |
+
"model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 194 |
+
"model.layers.22.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 195 |
+
"model.layers.22.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 196 |
+
"model.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 197 |
+
"model.layers.22.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 198 |
+
"model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 199 |
+
"model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 200 |
+
"model.layers.23.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 201 |
+
"model.layers.23.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 202 |
+
"model.layers.23.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 203 |
+
"model.layers.23.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 204 |
+
"model.layers.23.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 205 |
+
"model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 206 |
+
"model.layers.23.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 207 |
+
"model.layers.23.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 208 |
+
"model.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 209 |
+
"model.layers.23.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 210 |
+
"model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 211 |
+
"model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 212 |
+
"model.layers.24.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 213 |
+
"model.layers.24.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 214 |
+
"model.layers.24.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 215 |
+
"model.layers.24.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 216 |
+
"model.layers.24.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 217 |
+
"model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 218 |
+
"model.layers.24.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 219 |
+
"model.layers.24.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 220 |
+
"model.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 221 |
+
"model.layers.24.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 222 |
+
"model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 223 |
+
"model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 224 |
+
"model.layers.25.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 225 |
+
"model.layers.25.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 226 |
+
"model.layers.25.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 227 |
+
"model.layers.25.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 228 |
+
"model.layers.25.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 229 |
+
"model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 230 |
+
"model.layers.25.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 231 |
+
"model.layers.25.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 232 |
+
"model.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 233 |
+
"model.layers.25.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 234 |
+
"model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 235 |
+
"model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 236 |
+
"model.layers.26.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 237 |
+
"model.layers.26.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 238 |
+
"model.layers.26.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 239 |
+
"model.layers.26.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 240 |
+
"model.layers.26.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 241 |
+
"model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 242 |
+
"model.layers.26.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 243 |
+
"model.layers.26.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 244 |
+
"model.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 245 |
+
"model.layers.26.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 246 |
+
"model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 247 |
+
"model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 248 |
+
"model.layers.27.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 249 |
+
"model.layers.27.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 250 |
+
"model.layers.27.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 251 |
+
"model.layers.27.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 252 |
+
"model.layers.27.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 253 |
+
"model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 254 |
+
"model.layers.27.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 255 |
+
"model.layers.27.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 256 |
+
"model.layers.27.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 257 |
+
"model.layers.27.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 258 |
+
"model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 259 |
+
"model.layers.28.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 260 |
+
"model.layers.28.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 261 |
+
"model.layers.28.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 262 |
+
"model.layers.28.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 263 |
+
"model.layers.28.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 264 |
+
"model.layers.28.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 265 |
+
"model.layers.28.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 266 |
+
"model.layers.28.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 267 |
+
"model.layers.28.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 268 |
+
"model.layers.28.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 269 |
+
"model.layers.28.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 270 |
+
"model.layers.28.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 271 |
+
"model.layers.29.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 272 |
+
"model.layers.29.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 273 |
+
"model.layers.29.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 274 |
+
"model.layers.29.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 275 |
+
"model.layers.29.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 276 |
+
"model.layers.29.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 277 |
+
"model.layers.29.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 278 |
+
"model.layers.29.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 279 |
+
"model.layers.29.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 280 |
+
"model.layers.29.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 281 |
+
"model.layers.29.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 282 |
+
"model.layers.29.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 283 |
+
"model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 284 |
+
"model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 285 |
+
"model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 286 |
+
"model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 287 |
+
"model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 288 |
+
"model.layers.3.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 289 |
+
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 290 |
+
"model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 291 |
+
"model.layers.3.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 292 |
+
"model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 293 |
+
"model.layers.3.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 294 |
+
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 295 |
+
"model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 296 |
+
"model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 297 |
+
"model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 298 |
+
"model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 299 |
+
"model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 300 |
+
"model.layers.30.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 301 |
+
"model.layers.30.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 302 |
+
"model.layers.30.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 303 |
+
"model.layers.30.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 304 |
+
"model.layers.30.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 305 |
+
"model.layers.30.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 306 |
+
"model.layers.30.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 307 |
+
"model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 308 |
+
"model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 309 |
+
"model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 310 |
+
"model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 311 |
+
"model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 312 |
+
"model.layers.31.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 313 |
+
"model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 314 |
+
"model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 315 |
+
"model.layers.31.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 316 |
+
"model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 317 |
+
"model.layers.31.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 318 |
+
"model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 319 |
+
"model.layers.32.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 320 |
+
"model.layers.32.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 321 |
+
"model.layers.32.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 322 |
+
"model.layers.32.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 323 |
+
"model.layers.32.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 324 |
+
"model.layers.32.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 325 |
+
"model.layers.32.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 326 |
+
"model.layers.32.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 327 |
+
"model.layers.32.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 328 |
+
"model.layers.32.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 329 |
+
"model.layers.32.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 330 |
+
"model.layers.32.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 331 |
+
"model.layers.33.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 332 |
+
"model.layers.33.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 333 |
+
"model.layers.33.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 334 |
+
"model.layers.33.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 335 |
+
"model.layers.33.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 336 |
+
"model.layers.33.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 337 |
+
"model.layers.33.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 338 |
+
"model.layers.33.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 339 |
+
"model.layers.33.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 340 |
+
"model.layers.33.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 341 |
+
"model.layers.33.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 342 |
+
"model.layers.33.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 343 |
+
"model.layers.34.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 344 |
+
"model.layers.34.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 345 |
+
"model.layers.34.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 346 |
+
"model.layers.34.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 347 |
+
"model.layers.34.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 348 |
+
"model.layers.34.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 349 |
+
"model.layers.34.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 350 |
+
"model.layers.34.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 351 |
+
"model.layers.34.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 352 |
+
"model.layers.34.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 353 |
+
"model.layers.34.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 354 |
+
"model.layers.34.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 355 |
+
"model.layers.35.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 356 |
+
"model.layers.35.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
| 357 |
+
"model.layers.35.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
| 358 |
+
"model.layers.35.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
| 359 |
+
"model.layers.35.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
| 360 |
+
"model.layers.35.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
| 361 |
+
"model.layers.35.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
| 362 |
+
"model.layers.35.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
| 363 |
+
"model.layers.35.self_attn.q_proj.bias": "model-00002-of-00002.safetensors",
|
| 364 |
+
"model.layers.35.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
| 365 |
+
"model.layers.35.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
| 366 |
+
"model.layers.35.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
| 367 |
+
"model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 368 |
+
"model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 369 |
+
"model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 370 |
+
"model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 371 |
+
"model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 372 |
+
"model.layers.4.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 373 |
+
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 374 |
+
"model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 375 |
+
"model.layers.4.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 376 |
+
"model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 377 |
+
"model.layers.4.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 378 |
+
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 379 |
+
"model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 380 |
+
"model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 381 |
+
"model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 382 |
+
"model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 383 |
+
"model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 384 |
+
"model.layers.5.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 385 |
+
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 386 |
+
"model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 387 |
+
"model.layers.5.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 388 |
+
"model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 389 |
+
"model.layers.5.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 390 |
+
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 391 |
+
"model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 392 |
+
"model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 393 |
+
"model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 394 |
+
"model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 395 |
+
"model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 396 |
+
"model.layers.6.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 397 |
+
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 398 |
+
"model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 399 |
+
"model.layers.6.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 400 |
+
"model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 401 |
+
"model.layers.6.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 402 |
+
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 403 |
+
"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 404 |
+
"model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 405 |
+
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 406 |
+
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 407 |
+
"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 408 |
+
"model.layers.7.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 409 |
+
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 410 |
+
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 411 |
+
"model.layers.7.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 412 |
+
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 413 |
+
"model.layers.7.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 414 |
+
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 415 |
+
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 416 |
+
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 417 |
+
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 418 |
+
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 419 |
+
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 420 |
+
"model.layers.8.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 421 |
+
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 422 |
+
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 423 |
+
"model.layers.8.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 424 |
+
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 425 |
+
"model.layers.8.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 426 |
+
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 427 |
+
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 428 |
+
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
| 429 |
+
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
| 430 |
+
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
| 431 |
+
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
| 432 |
+
"model.layers.9.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
| 433 |
+
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
| 434 |
+
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
| 435 |
+
"model.layers.9.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
| 436 |
+
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
| 437 |
+
"model.layers.9.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
| 438 |
+
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
| 439 |
+
"model.norm.weight": "model-00002-of-00002.safetensors"
|
| 440 |
+
}
|
| 441 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|im_start|>",
|
| 4 |
+
"<|im_end|>",
|
| 5 |
+
"<|object_ref_start|>",
|
| 6 |
+
"<|object_ref_end|>",
|
| 7 |
+
"<|box_start|>",
|
| 8 |
+
"<|box_end|>",
|
| 9 |
+
"<|quad_start|>",
|
| 10 |
+
"<|quad_end|>",
|
| 11 |
+
"<|vision_start|>",
|
| 12 |
+
"<|vision_end|>",
|
| 13 |
+
"<|vision_pad|>",
|
| 14 |
+
"<|image_pad|>",
|
| 15 |
+
"<|video_pad|>"
|
| 16 |
+
],
|
| 17 |
+
"eos_token": {
|
| 18 |
+
"content": "<|im_end|>",
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
+
"single_word": false
|
| 23 |
+
},
|
| 24 |
+
"pad_token": {
|
| 25 |
+
"content": "<|endoftext|>",
|
| 26 |
+
"lstrip": false,
|
| 27 |
+
"normalized": false,
|
| 28 |
+
"rstrip": false,
|
| 29 |
+
"single_word": false
|
| 30 |
+
}
|
| 31 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5eee858c5123a4279c3e1f7b81247343f356ac767940b2692a928ad929543214
|
| 3 |
+
size 11422063
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"151644": {
|
| 14 |
+
"content": "<|im_start|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"151645": {
|
| 22 |
+
"content": "<|im_end|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"151646": {
|
| 30 |
+
"content": "<|object_ref_start|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"151647": {
|
| 38 |
+
"content": "<|object_ref_end|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"151648": {
|
| 46 |
+
"content": "<|box_start|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"151649": {
|
| 54 |
+
"content": "<|box_end|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"151650": {
|
| 62 |
+
"content": "<|quad_start|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"151651": {
|
| 70 |
+
"content": "<|quad_end|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"151652": {
|
| 78 |
+
"content": "<|vision_start|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": false,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"151653": {
|
| 86 |
+
"content": "<|vision_end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": false,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"151654": {
|
| 94 |
+
"content": "<|vision_pad|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": false,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"151655": {
|
| 102 |
+
"content": "<|image_pad|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": false,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"151656": {
|
| 110 |
+
"content": "<|video_pad|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": false,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
},
|
| 117 |
+
"151657": {
|
| 118 |
+
"content": "<tool_call>",
|
| 119 |
+
"lstrip": false,
|
| 120 |
+
"normalized": false,
|
| 121 |
+
"rstrip": false,
|
| 122 |
+
"single_word": false,
|
| 123 |
+
"special": false
|
| 124 |
+
},
|
| 125 |
+
"151658": {
|
| 126 |
+
"content": "</tool_call>",
|
| 127 |
+
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
+
"rstrip": false,
|
| 130 |
+
"single_word": false,
|
| 131 |
+
"special": false
|
| 132 |
+
},
|
| 133 |
+
"151659": {
|
| 134 |
+
"content": "<|fim_prefix|>",
|
| 135 |
+
"lstrip": false,
|
| 136 |
+
"normalized": false,
|
| 137 |
+
"rstrip": false,
|
| 138 |
+
"single_word": false,
|
| 139 |
+
"special": false
|
| 140 |
+
},
|
| 141 |
+
"151660": {
|
| 142 |
+
"content": "<|fim_middle|>",
|
| 143 |
+
"lstrip": false,
|
| 144 |
+
"normalized": false,
|
| 145 |
+
"rstrip": false,
|
| 146 |
+
"single_word": false,
|
| 147 |
+
"special": false
|
| 148 |
+
},
|
| 149 |
+
"151661": {
|
| 150 |
+
"content": "<|fim_suffix|>",
|
| 151 |
+
"lstrip": false,
|
| 152 |
+
"normalized": false,
|
| 153 |
+
"rstrip": false,
|
| 154 |
+
"single_word": false,
|
| 155 |
+
"special": false
|
| 156 |
+
},
|
| 157 |
+
"151662": {
|
| 158 |
+
"content": "<|fim_pad|>",
|
| 159 |
+
"lstrip": false,
|
| 160 |
+
"normalized": false,
|
| 161 |
+
"rstrip": false,
|
| 162 |
+
"single_word": false,
|
| 163 |
+
"special": false
|
| 164 |
+
},
|
| 165 |
+
"151663": {
|
| 166 |
+
"content": "<|repo_name|>",
|
| 167 |
+
"lstrip": false,
|
| 168 |
+
"normalized": false,
|
| 169 |
+
"rstrip": false,
|
| 170 |
+
"single_word": false,
|
| 171 |
+
"special": false
|
| 172 |
+
},
|
| 173 |
+
"151664": {
|
| 174 |
+
"content": "<|file_sep|>",
|
| 175 |
+
"lstrip": false,
|
| 176 |
+
"normalized": false,
|
| 177 |
+
"rstrip": false,
|
| 178 |
+
"single_word": false,
|
| 179 |
+
"special": false
|
| 180 |
+
}
|
| 181 |
+
},
|
| 182 |
+
"additional_special_tokens": [
|
| 183 |
+
"<|im_start|>",
|
| 184 |
+
"<|im_end|>",
|
| 185 |
+
"<|object_ref_start|>",
|
| 186 |
+
"<|object_ref_end|>",
|
| 187 |
+
"<|box_start|>",
|
| 188 |
+
"<|box_end|>",
|
| 189 |
+
"<|quad_start|>",
|
| 190 |
+
"<|quad_end|>",
|
| 191 |
+
"<|vision_start|>",
|
| 192 |
+
"<|vision_end|>",
|
| 193 |
+
"<|vision_pad|>",
|
| 194 |
+
"<|image_pad|>",
|
| 195 |
+
"<|video_pad|>"
|
| 196 |
+
],
|
| 197 |
+
"bos_token": null,
|
| 198 |
+
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
| 199 |
+
"clean_up_tokenization_spaces": false,
|
| 200 |
+
"eos_token": "<|im_end|>",
|
| 201 |
+
"errors": "replace",
|
| 202 |
+
"extra_special_tokens": {},
|
| 203 |
+
"model_max_length": 131072,
|
| 204 |
+
"pad_token": "<|endoftext|>",
|
| 205 |
+
"padding_side": "left",
|
| 206 |
+
"split_special_tokens": false,
|
| 207 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 208 |
+
"unk_token": null
|
| 209 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"total_flos": 0.0,
|
| 3 |
+
"train_loss": 0.11509215348958969,
|
| 4 |
+
"train_runtime": 61764.0604,
|
| 5 |
+
"train_samples": 7500,
|
| 6 |
+
"train_samples_per_second": 0.364,
|
| 7 |
+
"train_steps_per_second": 0.03
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,2479 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_metric": null,
|
| 3 |
+
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 3.0,
|
| 5 |
+
"eval_steps": 10,
|
| 6 |
+
"global_step": 1875,
|
| 7 |
+
"is_hyper_param_search": false,
|
| 8 |
+
"is_local_process_zero": true,
|
| 9 |
+
"is_world_process_zero": true,
|
| 10 |
+
"log_history": [
|
| 11 |
+
{
|
| 12 |
+
"completion_length": 549.5593883514405,
|
| 13 |
+
"epoch": 0.016,
|
| 14 |
+
"grad_norm": 0.6740879416465759,
|
| 15 |
+
"kl": 0.00035033226013183596,
|
| 16 |
+
"learning_rate": 1.5957446808510638e-07,
|
| 17 |
+
"loss": 0.0,
|
| 18 |
+
"reward": 0.42916667833924294,
|
| 19 |
+
"reward_std": 0.34028950408101083,
|
| 20 |
+
"rewards/accuracy_reward": 0.3166666737757623,
|
| 21 |
+
"rewards/format_reward": 0.11250000298023224,
|
| 22 |
+
"step": 10
|
| 23 |
+
},
|
| 24 |
+
{
|
| 25 |
+
"completion_length": 527.5224136352539,
|
| 26 |
+
"epoch": 0.032,
|
| 27 |
+
"grad_norm": 0.2563185691833496,
|
| 28 |
+
"kl": 0.0004585623741149902,
|
| 29 |
+
"learning_rate": 3.1914893617021275e-07,
|
| 30 |
+
"loss": 0.0,
|
| 31 |
+
"reward": 0.4945312611758709,
|
| 32 |
+
"reward_std": 0.35083559062331915,
|
| 33 |
+
"rewards/accuracy_reward": 0.37005209350027146,
|
| 34 |
+
"rewards/format_reward": 0.12447916958481073,
|
| 35 |
+
"step": 20
|
| 36 |
+
},
|
| 37 |
+
{
|
| 38 |
+
"completion_length": 538.003141784668,
|
| 39 |
+
"epoch": 0.048,
|
| 40 |
+
"grad_norm": 0.33752796053886414,
|
| 41 |
+
"kl": 0.005180943012237549,
|
| 42 |
+
"learning_rate": 4.787234042553192e-07,
|
| 43 |
+
"loss": 0.0002,
|
| 44 |
+
"reward": 0.5481770986691117,
|
| 45 |
+
"reward_std": 0.3370666664093733,
|
| 46 |
+
"rewards/accuracy_reward": 0.2927083420334384,
|
| 47 |
+
"rewards/format_reward": 0.25546875870786606,
|
| 48 |
+
"step": 30
|
| 49 |
+
},
|
| 50 |
+
{
|
| 51 |
+
"completion_length": 258.59141426086427,
|
| 52 |
+
"epoch": 0.064,
|
| 53 |
+
"grad_norm": 0.354353666305542,
|
| 54 |
+
"kl": 0.0585662841796875,
|
| 55 |
+
"learning_rate": 6.382978723404255e-07,
|
| 56 |
+
"loss": 0.0023,
|
| 57 |
+
"reward": 0.8239583492279052,
|
| 58 |
+
"reward_std": 0.27262834142893555,
|
| 59 |
+
"rewards/accuracy_reward": 0.06171875221189112,
|
| 60 |
+
"rewards/format_reward": 0.7622395977377892,
|
| 61 |
+
"step": 40
|
| 62 |
+
},
|
| 63 |
+
{
|
| 64 |
+
"completion_length": 161.72448558807372,
|
| 65 |
+
"epoch": 0.08,
|
| 66 |
+
"grad_norm": 0.24595139920711517,
|
| 67 |
+
"kl": 0.0718231201171875,
|
| 68 |
+
"learning_rate": 7.978723404255319e-07,
|
| 69 |
+
"loss": 0.0029,
|
| 70 |
+
"reward": 0.9528646096587181,
|
| 71 |
+
"reward_std": 0.18603200055658817,
|
| 72 |
+
"rewards/accuracy_reward": 0.020572917093522845,
|
| 73 |
+
"rewards/format_reward": 0.9322916835546493,
|
| 74 |
+
"step": 50
|
| 75 |
+
},
|
| 76 |
+
{
|
| 77 |
+
"completion_length": 187.65990085601806,
|
| 78 |
+
"epoch": 0.096,
|
| 79 |
+
"grad_norm": 0.18100768327713013,
|
| 80 |
+
"kl": 0.0560791015625,
|
| 81 |
+
"learning_rate": 9.574468085106384e-07,
|
| 82 |
+
"loss": 0.0022,
|
| 83 |
+
"reward": 0.9700521141290664,
|
| 84 |
+
"reward_std": 0.23906342964619398,
|
| 85 |
+
"rewards/accuracy_reward": 0.05546875142026693,
|
| 86 |
+
"rewards/format_reward": 0.9145833522081375,
|
| 87 |
+
"step": 60
|
| 88 |
+
},
|
| 89 |
+
{
|
| 90 |
+
"completion_length": 197.76198501586913,
|
| 91 |
+
"epoch": 0.112,
|
| 92 |
+
"grad_norm": 0.2552257180213928,
|
| 93 |
+
"kl": 0.067510986328125,
|
| 94 |
+
"learning_rate": 1.1170212765957447e-06,
|
| 95 |
+
"loss": 0.0027,
|
| 96 |
+
"reward": 1.0585937827825547,
|
| 97 |
+
"reward_std": 0.278127851895988,
|
| 98 |
+
"rewards/accuracy_reward": 0.11562500302679837,
|
| 99 |
+
"rewards/format_reward": 0.9429687693715095,
|
| 100 |
+
"step": 70
|
| 101 |
+
},
|
| 102 |
+
{
|
| 103 |
+
"completion_length": 207.72917366027832,
|
| 104 |
+
"epoch": 0.128,
|
| 105 |
+
"grad_norm": 0.23932258784770966,
|
| 106 |
+
"kl": 0.08233642578125,
|
| 107 |
+
"learning_rate": 1.276595744680851e-06,
|
| 108 |
+
"loss": 0.0033,
|
| 109 |
+
"reward": 1.1739583641290665,
|
| 110 |
+
"reward_std": 0.31914406083524227,
|
| 111 |
+
"rewards/accuracy_reward": 0.2052083393326029,
|
| 112 |
+
"rewards/format_reward": 0.9687500178813935,
|
| 113 |
+
"step": 80
|
| 114 |
+
},
|
| 115 |
+
{
|
| 116 |
+
"completion_length": 254.02891464233397,
|
| 117 |
+
"epoch": 0.144,
|
| 118 |
+
"grad_norm": 0.13784578442573547,
|
| 119 |
+
"kl": 0.077899169921875,
|
| 120 |
+
"learning_rate": 1.4361702127659576e-06,
|
| 121 |
+
"loss": 0.0031,
|
| 122 |
+
"reward": 1.254687537252903,
|
| 123 |
+
"reward_std": 0.3285429562442005,
|
| 124 |
+
"rewards/accuracy_reward": 0.2760416746838018,
|
| 125 |
+
"rewards/format_reward": 0.9786458492279053,
|
| 126 |
+
"step": 90
|
| 127 |
+
},
|
| 128 |
+
{
|
| 129 |
+
"completion_length": 313.156778717041,
|
| 130 |
+
"epoch": 0.16,
|
| 131 |
+
"grad_norm": 0.14116181433200836,
|
| 132 |
+
"kl": 0.087481689453125,
|
| 133 |
+
"learning_rate": 1.5957446808510639e-06,
|
| 134 |
+
"loss": 0.0035,
|
| 135 |
+
"reward": 1.398958370089531,
|
| 136 |
+
"reward_std": 0.364690675213933,
|
| 137 |
+
"rewards/accuracy_reward": 0.43567709643393754,
|
| 138 |
+
"rewards/format_reward": 0.9632812708616256,
|
| 139 |
+
"step": 100
|
| 140 |
+
},
|
| 141 |
+
{
|
| 142 |
+
"completion_length": 317.794021987915,
|
| 143 |
+
"epoch": 0.176,
|
| 144 |
+
"grad_norm": 0.17862962186336517,
|
| 145 |
+
"kl": 0.09073486328125,
|
| 146 |
+
"learning_rate": 1.7553191489361702e-06,
|
| 147 |
+
"loss": 0.0036,
|
| 148 |
+
"reward": 1.4677083671092988,
|
| 149 |
+
"reward_std": 0.37521998956799507,
|
| 150 |
+
"rewards/accuracy_reward": 0.517708345875144,
|
| 151 |
+
"rewards/format_reward": 0.9500000178813934,
|
| 152 |
+
"step": 110
|
| 153 |
+
},
|
| 154 |
+
{
|
| 155 |
+
"completion_length": 310.7653747558594,
|
| 156 |
+
"epoch": 0.192,
|
| 157 |
+
"grad_norm": 0.160443514585495,
|
| 158 |
+
"kl": 0.095281982421875,
|
| 159 |
+
"learning_rate": 1.9148936170212767e-06,
|
| 160 |
+
"loss": 0.0038,
|
| 161 |
+
"reward": 1.5169271260499955,
|
| 162 |
+
"reward_std": 0.3428271571174264,
|
| 163 |
+
"rewards/accuracy_reward": 0.5375000145286322,
|
| 164 |
+
"rewards/format_reward": 0.979427094757557,
|
| 165 |
+
"step": 120
|
| 166 |
+
},
|
| 167 |
+
{
|
| 168 |
+
"completion_length": 293.892195892334,
|
| 169 |
+
"epoch": 0.208,
|
| 170 |
+
"grad_norm": 0.12249578535556793,
|
| 171 |
+
"kl": 0.093798828125,
|
| 172 |
+
"learning_rate": 2.074468085106383e-06,
|
| 173 |
+
"loss": 0.0037,
|
| 174 |
+
"reward": 1.5312500417232513,
|
| 175 |
+
"reward_std": 0.3389985624700785,
|
| 176 |
+
"rewards/accuracy_reward": 0.539322929829359,
|
| 177 |
+
"rewards/format_reward": 0.9919271007180214,
|
| 178 |
+
"step": 130
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"completion_length": 325.6273529052734,
|
| 182 |
+
"epoch": 0.224,
|
| 183 |
+
"grad_norm": 0.14869874715805054,
|
| 184 |
+
"kl": 0.08721923828125,
|
| 185 |
+
"learning_rate": 2.2340425531914894e-06,
|
| 186 |
+
"loss": 0.0035,
|
| 187 |
+
"reward": 1.4973958760499955,
|
| 188 |
+
"reward_std": 0.32006428195163605,
|
| 189 |
+
"rewards/accuracy_reward": 0.5270833484828472,
|
| 190 |
+
"rewards/format_reward": 0.9703125178813934,
|
| 191 |
+
"step": 140
|
| 192 |
+
},
|
| 193 |
+
{
|
| 194 |
+
"completion_length": 302.0961029052734,
|
| 195 |
+
"epoch": 0.24,
|
| 196 |
+
"grad_norm": 0.15774066746234894,
|
| 197 |
+
"kl": 0.09039306640625,
|
| 198 |
+
"learning_rate": 2.3936170212765957e-06,
|
| 199 |
+
"loss": 0.0036,
|
| 200 |
+
"reward": 1.546093797683716,
|
| 201 |
+
"reward_std": 0.33077279273420573,
|
| 202 |
+
"rewards/accuracy_reward": 0.5557291835546494,
|
| 203 |
+
"rewards/format_reward": 0.9903646007180213,
|
| 204 |
+
"step": 150
|
| 205 |
+
},
|
| 206 |
+
{
|
| 207 |
+
"completion_length": 377.5010528564453,
|
| 208 |
+
"epoch": 0.256,
|
| 209 |
+
"grad_norm": 0.1264476478099823,
|
| 210 |
+
"kl": 0.083544921875,
|
| 211 |
+
"learning_rate": 2.553191489361702e-06,
|
| 212 |
+
"loss": 0.0033,
|
| 213 |
+
"reward": 1.4979167014360428,
|
| 214 |
+
"reward_std": 0.3458104237914085,
|
| 215 |
+
"rewards/accuracy_reward": 0.5213541844394058,
|
| 216 |
+
"rewards/format_reward": 0.9765625163912773,
|
| 217 |
+
"step": 160
|
| 218 |
+
},
|
| 219 |
+
{
|
| 220 |
+
"completion_length": 333.62370681762695,
|
| 221 |
+
"epoch": 0.272,
|
| 222 |
+
"grad_norm": 0.0962129607796669,
|
| 223 |
+
"kl": 0.0868896484375,
|
| 224 |
+
"learning_rate": 2.7127659574468088e-06,
|
| 225 |
+
"loss": 0.0035,
|
| 226 |
+
"reward": 1.55364588201046,
|
| 227 |
+
"reward_std": 0.3210131399333477,
|
| 228 |
+
"rewards/accuracy_reward": 0.5757812647148967,
|
| 229 |
+
"rewards/format_reward": 0.9778646036982537,
|
| 230 |
+
"step": 170
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"completion_length": 372.2838665008545,
|
| 234 |
+
"epoch": 0.288,
|
| 235 |
+
"grad_norm": 0.23018397390842438,
|
| 236 |
+
"kl": 0.09453125,
|
| 237 |
+
"learning_rate": 2.872340425531915e-06,
|
| 238 |
+
"loss": 0.0038,
|
| 239 |
+
"reward": 1.533854204416275,
|
| 240 |
+
"reward_std": 0.3298664506524801,
|
| 241 |
+
"rewards/accuracy_reward": 0.5500000137835741,
|
| 242 |
+
"rewards/format_reward": 0.9838541820645332,
|
| 243 |
+
"step": 180
|
| 244 |
+
},
|
| 245 |
+
{
|
| 246 |
+
"completion_length": 352.70756072998046,
|
| 247 |
+
"epoch": 0.304,
|
| 248 |
+
"grad_norm": 0.14402048289775848,
|
| 249 |
+
"kl": 0.0962158203125,
|
| 250 |
+
"learning_rate": 2.999989596239813e-06,
|
| 251 |
+
"loss": 0.0039,
|
| 252 |
+
"reward": 1.5427083760499953,
|
| 253 |
+
"reward_std": 0.3494082003831863,
|
| 254 |
+
"rewards/accuracy_reward": 0.575781268440187,
|
| 255 |
+
"rewards/format_reward": 0.9669270977377892,
|
| 256 |
+
"step": 190
|
| 257 |
+
},
|
| 258 |
+
{
|
| 259 |
+
"completion_length": 340.1216236114502,
|
| 260 |
+
"epoch": 0.32,
|
| 261 |
+
"grad_norm": 0.12887056171894073,
|
| 262 |
+
"kl": 0.12586669921875,
|
| 263 |
+
"learning_rate": 2.9996254797863878e-06,
|
| 264 |
+
"loss": 0.005,
|
| 265 |
+
"reward": 1.4958333730697633,
|
| 266 |
+
"reward_std": 0.3522159656509757,
|
| 267 |
+
"rewards/accuracy_reward": 0.5208333488553762,
|
| 268 |
+
"rewards/format_reward": 0.9750000193715096,
|
| 269 |
+
"step": 200
|
| 270 |
+
},
|
| 271 |
+
{
|
| 272 |
+
"completion_length": 345.5015693664551,
|
| 273 |
+
"epoch": 0.336,
|
| 274 |
+
"grad_norm": 0.1841161698102951,
|
| 275 |
+
"kl": 0.13616943359375,
|
| 276 |
+
"learning_rate": 2.9987413196322384e-06,
|
| 277 |
+
"loss": 0.0054,
|
| 278 |
+
"reward": 1.5750000387430192,
|
| 279 |
+
"reward_std": 0.3604385921731591,
|
| 280 |
+
"rewards/accuracy_reward": 0.6200521003454924,
|
| 281 |
+
"rewards/format_reward": 0.9549479350447655,
|
| 282 |
+
"step": 210
|
| 283 |
+
},
|
| 284 |
+
{
|
| 285 |
+
"completion_length": 351.95599975585935,
|
| 286 |
+
"epoch": 0.352,
|
| 287 |
+
"grad_norm": 0.21690769493579865,
|
| 288 |
+
"kl": 0.113519287109375,
|
| 289 |
+
"learning_rate": 2.9973374223885316e-06,
|
| 290 |
+
"loss": 0.0045,
|
| 291 |
+
"reward": 1.456250038743019,
|
| 292 |
+
"reward_std": 0.3830007821321487,
|
| 293 |
+
"rewards/accuracy_reward": 0.5210937664844095,
|
| 294 |
+
"rewards/format_reward": 0.9351562723517418,
|
| 295 |
+
"step": 220
|
| 296 |
+
},
|
| 297 |
+
{
|
| 298 |
+
"completion_length": 338.8109489440918,
|
| 299 |
+
"epoch": 0.368,
|
| 300 |
+
"grad_norm": 0.15305453538894653,
|
| 301 |
+
"kl": 0.15860595703125,
|
| 302 |
+
"learning_rate": 2.9954142749021024e-06,
|
| 303 |
+
"loss": 0.0063,
|
| 304 |
+
"reward": 1.4955729603767396,
|
| 305 |
+
"reward_std": 0.3856545228511095,
|
| 306 |
+
"rewards/accuracy_reward": 0.540625018067658,
|
| 307 |
+
"rewards/format_reward": 0.9549479365348816,
|
| 308 |
+
"step": 230
|
| 309 |
+
},
|
| 310 |
+
{
|
| 311 |
+
"completion_length": 340.34349899291993,
|
| 312 |
+
"epoch": 0.384,
|
| 313 |
+
"grad_norm": 0.12304379045963287,
|
| 314 |
+
"kl": 0.13148193359375,
|
| 315 |
+
"learning_rate": 2.9929725440866226e-06,
|
| 316 |
+
"loss": 0.0053,
|
| 317 |
+
"reward": 1.5273437917232513,
|
| 318 |
+
"reward_std": 0.33333041463047264,
|
| 319 |
+
"rewards/accuracy_reward": 0.5708333509741351,
|
| 320 |
+
"rewards/format_reward": 0.9565104365348815,
|
| 321 |
+
"step": 240
|
| 322 |
+
},
|
| 323 |
+
{
|
| 324 |
+
"completion_length": 328.22422676086427,
|
| 325 |
+
"epoch": 0.4,
|
| 326 |
+
"grad_norm": 0.1456129401922226,
|
| 327 |
+
"kl": 0.16090087890625,
|
| 328 |
+
"learning_rate": 2.990013076691329e-06,
|
| 329 |
+
"loss": 0.0064,
|
| 330 |
+
"reward": 1.4192708760499955,
|
| 331 |
+
"reward_std": 0.38170270454138516,
|
| 332 |
+
"rewards/accuracy_reward": 0.48046876322478055,
|
| 333 |
+
"rewards/format_reward": 0.9388021036982537,
|
| 334 |
+
"step": 250
|
| 335 |
+
},
|
| 336 |
+
{
|
| 337 |
+
"completion_length": 346.2437599182129,
|
| 338 |
+
"epoch": 0.416,
|
| 339 |
+
"grad_norm": 0.14456409215927124,
|
| 340 |
+
"kl": 0.15968017578125,
|
| 341 |
+
"learning_rate": 2.986536899007383e-06,
|
| 342 |
+
"loss": 0.0064,
|
| 343 |
+
"reward": 1.4953125447034836,
|
| 344 |
+
"reward_std": 0.4336598340421915,
|
| 345 |
+
"rewards/accuracy_reward": 0.6145833546295763,
|
| 346 |
+
"rewards/format_reward": 0.8807291924953461,
|
| 347 |
+
"step": 260
|
| 348 |
+
},
|
| 349 |
+
{
|
| 350 |
+
"completion_length": 269.3726661682129,
|
| 351 |
+
"epoch": 0.432,
|
| 352 |
+
"grad_norm": 0.46196305751800537,
|
| 353 |
+
"kl": 0.2087890625,
|
| 354 |
+
"learning_rate": 2.982545216511974e-06,
|
| 355 |
+
"loss": 0.0084,
|
| 356 |
+
"reward": 1.3755208745598793,
|
| 357 |
+
"reward_std": 0.399412408657372,
|
| 358 |
+
"rewards/accuracy_reward": 0.46328125838190315,
|
| 359 |
+
"rewards/format_reward": 0.9122396051883698,
|
| 360 |
+
"step": 270
|
| 361 |
+
},
|
| 362 |
+
{
|
| 363 |
+
"completion_length": 343.7578243255615,
|
| 364 |
+
"epoch": 0.448,
|
| 365 |
+
"grad_norm": 0.14162611961364746,
|
| 366 |
+
"kl": 0.259228515625,
|
| 367 |
+
"learning_rate": 2.978039413450278e-06,
|
| 368 |
+
"loss": 0.0104,
|
| 369 |
+
"reward": 1.2468750298023223,
|
| 370 |
+
"reward_std": 0.5331707052886486,
|
| 371 |
+
"rewards/accuracy_reward": 0.40807292954996227,
|
| 372 |
+
"rewards/format_reward": 0.8388021022081376,
|
| 373 |
+
"step": 280
|
| 374 |
+
},
|
| 375 |
+
{
|
| 376 |
+
"completion_length": 283.88282241821287,
|
| 377 |
+
"epoch": 0.464,
|
| 378 |
+
"grad_norm": 0.12917938828468323,
|
| 379 |
+
"kl": 0.24149169921875,
|
| 380 |
+
"learning_rate": 2.9730210523554276e-06,
|
| 381 |
+
"loss": 0.0097,
|
| 382 |
+
"reward": 1.4640625447034836,
|
| 383 |
+
"reward_std": 0.39531214712187646,
|
| 384 |
+
"rewards/accuracy_reward": 0.5385416830889881,
|
| 385 |
+
"rewards/format_reward": 0.9255208507180214,
|
| 386 |
+
"step": 290
|
| 387 |
+
},
|
| 388 |
+
{
|
| 389 |
+
"completion_length": 348.46693687438966,
|
| 390 |
+
"epoch": 0.48,
|
| 391 |
+
"grad_norm": 0.10320460051298141,
|
| 392 |
+
"kl": 0.212744140625,
|
| 393 |
+
"learning_rate": 2.967491873506653e-06,
|
| 394 |
+
"loss": 0.0085,
|
| 395 |
+
"reward": 1.4231771245598792,
|
| 396 |
+
"reward_std": 0.4722843859344721,
|
| 397 |
+
"rewards/accuracy_reward": 0.5325520962476731,
|
| 398 |
+
"rewards/format_reward": 0.8906250193715095,
|
| 399 |
+
"step": 300
|
| 400 |
+
},
|
| 401 |
+
{
|
| 402 |
+
"completion_length": 385.8747501373291,
|
| 403 |
+
"epoch": 0.496,
|
| 404 |
+
"grad_norm": 0.09853401780128479,
|
| 405 |
+
"kl": 0.2241943359375,
|
| 406 |
+
"learning_rate": 2.9614537943257835e-06,
|
| 407 |
+
"loss": 0.009,
|
| 408 |
+
"reward": 1.4325521185994148,
|
| 409 |
+
"reward_std": 0.48100620210170747,
|
| 410 |
+
"rewards/accuracy_reward": 0.5578125163912773,
|
| 411 |
+
"rewards/format_reward": 0.8747396007180214,
|
| 412 |
+
"step": 310
|
| 413 |
+
},
|
| 414 |
+
{
|
| 415 |
+
"completion_length": 340.27865371704104,
|
| 416 |
+
"epoch": 0.512,
|
| 417 |
+
"grad_norm": 240231.90625,
|
| 418 |
+
"kl": 4838.629223632813,
|
| 419 |
+
"learning_rate": 2.9549089087123195e-06,
|
| 420 |
+
"loss": 193.2151,
|
| 421 |
+
"reward": 1.402343785762787,
|
| 422 |
+
"reward_std": 0.49140210878103974,
|
| 423 |
+
"rewards/accuracy_reward": 0.5153646014630795,
|
| 424 |
+
"rewards/format_reward": 0.8869791895151138,
|
| 425 |
+
"step": 320
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"completion_length": 385.4213642120361,
|
| 429 |
+
"epoch": 0.528,
|
| 430 |
+
"grad_norm": 0.07590307295322418,
|
| 431 |
+
"kl": 12.74246826171875,
|
| 432 |
+
"learning_rate": 2.947859486317304e-06,
|
| 433 |
+
"loss": 0.5097,
|
| 434 |
+
"reward": 1.433593787252903,
|
| 435 |
+
"reward_std": 0.5454600352793932,
|
| 436 |
+
"rewards/accuracy_reward": 0.5776041799690574,
|
| 437 |
+
"rewards/format_reward": 0.8559896066784859,
|
| 438 |
+
"step": 330
|
| 439 |
+
},
|
| 440 |
+
{
|
| 441 |
+
"completion_length": 366.5921993255615,
|
| 442 |
+
"epoch": 0.544,
|
| 443 |
+
"grad_norm": 0.0868915244936943,
|
| 444 |
+
"kl": 0.27060546875,
|
| 445 |
+
"learning_rate": 2.9403079717562495e-06,
|
| 446 |
+
"loss": 0.0108,
|
| 447 |
+
"reward": 1.4158854514360428,
|
| 448 |
+
"reward_std": 0.5097951695322991,
|
| 449 |
+
"rewards/accuracy_reward": 0.5526041839271784,
|
| 450 |
+
"rewards/format_reward": 0.8632812693715095,
|
| 451 |
+
"step": 340
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"completion_length": 342.1976657867432,
|
| 455 |
+
"epoch": 0.56,
|
| 456 |
+
"grad_norm": 0.09720102697610855,
|
| 457 |
+
"kl": 0.24512939453125,
|
| 458 |
+
"learning_rate": 2.9322569837613867e-06,
|
| 459 |
+
"loss": 0.0098,
|
| 460 |
+
"reward": 1.4158854573965072,
|
| 461 |
+
"reward_std": 0.4330069116316736,
|
| 462 |
+
"rewards/accuracy_reward": 0.5171875095693395,
|
| 463 |
+
"rewards/format_reward": 0.8986979350447655,
|
| 464 |
+
"step": 350
|
| 465 |
+
},
|
| 466 |
+
{
|
| 467 |
+
"completion_length": 304.5101634979248,
|
| 468 |
+
"epoch": 0.576,
|
| 469 |
+
"grad_norm": 0.1557752639055252,
|
| 470 |
+
"kl": 0.273779296875,
|
| 471 |
+
"learning_rate": 2.9237093142735355e-06,
|
| 472 |
+
"loss": 0.011,
|
| 473 |
+
"reward": 1.4440104573965074,
|
| 474 |
+
"reward_std": 0.45580658232793214,
|
| 475 |
+
"rewards/accuracy_reward": 0.5408854335546494,
|
| 476 |
+
"rewards/format_reward": 0.9031250193715096,
|
| 477 |
+
"step": 360
|
| 478 |
+
},
|
| 479 |
+
{
|
| 480 |
+
"completion_length": 337.13073883056643,
|
| 481 |
+
"epoch": 0.592,
|
| 482 |
+
"grad_norm": 0.07957520335912704,
|
| 483 |
+
"kl": 0.2844482421875,
|
| 484 |
+
"learning_rate": 2.914667927473909e-06,
|
| 485 |
+
"loss": 0.0114,
|
| 486 |
+
"reward": 1.4494792118668556,
|
| 487 |
+
"reward_std": 0.4396442363038659,
|
| 488 |
+
"rewards/accuracy_reward": 0.5385416800854728,
|
| 489 |
+
"rewards/format_reward": 0.9109375163912773,
|
| 490 |
+
"step": 370
|
| 491 |
+
},
|
| 492 |
+
{
|
| 493 |
+
"completion_length": 348.5554767608643,
|
| 494 |
+
"epoch": 0.608,
|
| 495 |
+
"grad_norm": 0.10430486500263214,
|
| 496 |
+
"kl": 0.2727783203125,
|
| 497 |
+
"learning_rate": 2.905135958756186e-06,
|
| 498 |
+
"loss": 0.0109,
|
| 499 |
+
"reward": 1.416666714847088,
|
| 500 |
+
"reward_std": 0.5037212844938039,
|
| 501 |
+
"rewards/accuracy_reward": 0.5440104316920042,
|
| 502 |
+
"rewards/format_reward": 0.8726562723517418,
|
| 503 |
+
"step": 380
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"completion_length": 296.6213638305664,
|
| 507 |
+
"epoch": 0.624,
|
| 508 |
+
"grad_norm": 0.1668756604194641,
|
| 509 |
+
"kl": 1331.5044677734375,
|
| 510 |
+
"learning_rate": 2.8951167136392134e-06,
|
| 511 |
+
"loss": 53.281,
|
| 512 |
+
"reward": 1.3690104529261589,
|
| 513 |
+
"reward_std": 0.5218944691121579,
|
| 514 |
+
"rewards/accuracy_reward": 0.49401043094694613,
|
| 515 |
+
"rewards/format_reward": 0.8750000208616256,
|
| 516 |
+
"step": 390
|
| 517 |
+
},
|
| 518 |
+
{
|
| 519 |
+
"completion_length": 283.71016426086425,
|
| 520 |
+
"epoch": 0.64,
|
| 521 |
+
"grad_norm": 0.11033165454864502,
|
| 522 |
+
"kl": 0.2045654296875,
|
| 523 |
+
"learning_rate": 2.8846136666207118e-06,
|
| 524 |
+
"loss": 0.0082,
|
| 525 |
+
"reward": 1.5940104514360427,
|
| 526 |
+
"reward_std": 0.36332854218780997,
|
| 527 |
+
"rewards/accuracy_reward": 0.6401041854172945,
|
| 528 |
+
"rewards/format_reward": 0.9539062738418579,
|
| 529 |
+
"step": 400
|
| 530 |
+
},
|
| 531 |
+
{
|
| 532 |
+
"completion_length": 357.7877712249756,
|
| 533 |
+
"epoch": 0.656,
|
| 534 |
+
"grad_norm": 0.1104319766163826,
|
| 535 |
+
"kl": 74.237353515625,
|
| 536 |
+
"learning_rate": 2.873630459972376e-06,
|
| 537 |
+
"loss": 2.9658,
|
| 538 |
+
"reward": 1.471875038743019,
|
| 539 |
+
"reward_std": 0.4806873705238104,
|
| 540 |
+
"rewards/accuracy_reward": 0.5885416785255074,
|
| 541 |
+
"rewards/format_reward": 0.8833333522081375,
|
| 542 |
+
"step": 410
|
| 543 |
+
},
|
| 544 |
+
{
|
| 545 |
+
"completion_length": 314.5830821990967,
|
| 546 |
+
"epoch": 0.672,
|
| 547 |
+
"grad_norm": 0.1443065106868744,
|
| 548 |
+
"kl": 1.9264404296875,
|
| 549 |
+
"learning_rate": 2.8621709024768054e-06,
|
| 550 |
+
"loss": 0.0774,
|
| 551 |
+
"reward": 1.4846354559063912,
|
| 552 |
+
"reward_std": 0.4601195017807186,
|
| 553 |
+
"rewards/accuracy_reward": 0.578645845502615,
|
| 554 |
+
"rewards/format_reward": 0.9059896066784858,
|
| 555 |
+
"step": 420
|
| 556 |
+
},
|
| 557 |
+
{
|
| 558 |
+
"completion_length": 352.45912475585936,
|
| 559 |
+
"epoch": 0.688,
|
| 560 |
+
"grad_norm": 0.08876121789216995,
|
| 561 |
+
"kl": 0.278662109375,
|
| 562 |
+
"learning_rate": 2.8502389681066806e-06,
|
| 563 |
+
"loss": 0.0111,
|
| 564 |
+
"reward": 1.4117187947034835,
|
| 565 |
+
"reward_std": 0.46184736788272857,
|
| 566 |
+
"rewards/accuracy_reward": 0.5140625171363353,
|
| 567 |
+
"rewards/format_reward": 0.8976562708616257,
|
| 568 |
+
"step": 430
|
| 569 |
+
},
|
| 570 |
+
{
|
| 571 |
+
"completion_length": 285.142195892334,
|
| 572 |
+
"epoch": 0.704,
|
| 573 |
+
"grad_norm": 0.07999342679977417,
|
| 574 |
+
"kl": 2598.7319091796876,
|
| 575 |
+
"learning_rate": 2.8378387946466623e-06,
|
| 576 |
+
"loss": 103.7532,
|
| 577 |
+
"reward": 1.3726562917232514,
|
| 578 |
+
"reward_std": 0.49423595853149893,
|
| 579 |
+
"rewards/accuracy_reward": 0.47968751210719346,
|
| 580 |
+
"rewards/format_reward": 0.8929687663912773,
|
| 581 |
+
"step": 440
|
| 582 |
+
},
|
| 583 |
+
{
|
| 584 |
+
"completion_length": 417.71849822998047,
|
| 585 |
+
"epoch": 0.72,
|
| 586 |
+
"grad_norm": 0.08980146795511246,
|
| 587 |
+
"kl": 0.1867431640625,
|
| 588 |
+
"learning_rate": 2.8249746822584788e-06,
|
| 589 |
+
"loss": 0.0075,
|
| 590 |
+
"reward": 1.4705729529261589,
|
| 591 |
+
"reward_std": 0.4550738349556923,
|
| 592 |
+
"rewards/accuracy_reward": 0.5778646010905504,
|
| 593 |
+
"rewards/format_reward": 0.8927083507180213,
|
| 594 |
+
"step": 450
|
| 595 |
+
},
|
| 596 |
+
{
|
| 597 |
+
"completion_length": 499.32371215820314,
|
| 598 |
+
"epoch": 0.736,
|
| 599 |
+
"grad_norm": 0.09107893705368042,
|
| 600 |
+
"kl": 0.347216796875,
|
| 601 |
+
"learning_rate": 2.811651091989708e-06,
|
| 602 |
+
"loss": 0.0139,
|
| 603 |
+
"reward": 1.2427083723247052,
|
| 604 |
+
"reward_std": 0.6114235140383244,
|
| 605 |
+
"rewards/accuracy_reward": 0.48880209363996985,
|
| 606 |
+
"rewards/format_reward": 0.7539062686264515,
|
| 607 |
+
"step": 460
|
| 608 |
+
},
|
| 609 |
+
{
|
| 610 |
+
"completion_length": 363.605997467041,
|
| 611 |
+
"epoch": 0.752,
|
| 612 |
+
"grad_norm": 0.10554559528827667,
|
| 613 |
+
"kl": 1.361376953125,
|
| 614 |
+
"learning_rate": 2.797872644226761e-06,
|
| 615 |
+
"loss": 0.0545,
|
| 616 |
+
"reward": 1.5098958760499954,
|
| 617 |
+
"reward_std": 0.38472358537837864,
|
| 618 |
+
"rewards/accuracy_reward": 0.5791666805744171,
|
| 619 |
+
"rewards/format_reward": 0.9307291820645333,
|
| 620 |
+
"step": 470
|
| 621 |
+
},
|
| 622 |
+
{
|
| 623 |
+
"completion_length": 343.4364669799805,
|
| 624 |
+
"epoch": 0.768,
|
| 625 |
+
"grad_norm": 0.08596952259540558,
|
| 626 |
+
"kl": 0.2862548828125,
|
| 627 |
+
"learning_rate": 2.7836441170926177e-06,
|
| 628 |
+
"loss": 0.0114,
|
| 629 |
+
"reward": 1.4947917029261588,
|
| 630 |
+
"reward_std": 0.45332635566592216,
|
| 631 |
+
"rewards/accuracy_reward": 0.5903646016027778,
|
| 632 |
+
"rewards/format_reward": 0.904427108168602,
|
| 633 |
+
"step": 480
|
| 634 |
+
},
|
| 635 |
+
{
|
| 636 |
+
"completion_length": 372.5755313873291,
|
| 637 |
+
"epoch": 0.784,
|
| 638 |
+
"grad_norm": 0.12259896844625473,
|
| 639 |
+
"kl": 0.3115966796875,
|
| 640 |
+
"learning_rate": 2.768970444789855e-06,
|
| 641 |
+
"loss": 0.0125,
|
| 642 |
+
"reward": 1.3859375461935997,
|
| 643 |
+
"reward_std": 0.5074398431926965,
|
| 644 |
+
"rewards/accuracy_reward": 0.521354182693176,
|
| 645 |
+
"rewards/format_reward": 0.8645833596587181,
|
| 646 |
+
"step": 490
|
| 647 |
+
},
|
| 648 |
+
{
|
| 649 |
+
"completion_length": 343.65287551879885,
|
| 650 |
+
"epoch": 0.8,
|
| 651 |
+
"grad_norm": 0.32125625014305115,
|
| 652 |
+
"kl": 0.2789794921875,
|
| 653 |
+
"learning_rate": 2.753856715889552e-06,
|
| 654 |
+
"loss": 0.0112,
|
| 655 |
+
"reward": 1.3770833745598794,
|
| 656 |
+
"reward_std": 0.5012526127509773,
|
| 657 |
+
"rewards/accuracy_reward": 0.5059895979240536,
|
| 658 |
+
"rewards/format_reward": 0.8710937723517418,
|
| 659 |
+
"step": 500
|
| 660 |
+
},
|
| 661 |
+
{
|
| 662 |
+
"completion_length": 250.93281898498535,
|
| 663 |
+
"epoch": 0.816,
|
| 664 |
+
"grad_norm": 0.19703888893127441,
|
| 665 |
+
"kl": 4480.266870117188,
|
| 666 |
+
"learning_rate": 2.738308171566667e-06,
|
| 667 |
+
"loss": 179.2807,
|
| 668 |
+
"reward": 1.4348958730697632,
|
| 669 |
+
"reward_std": 0.4180175280198455,
|
| 670 |
+
"rewards/accuracy_reward": 0.4963541803881526,
|
| 671 |
+
"rewards/format_reward": 0.9385416880249977,
|
| 672 |
+
"step": 510
|
| 673 |
+
},
|
| 674 |
+
{
|
| 675 |
+
"completion_length": 276.1153732299805,
|
| 676 |
+
"epoch": 0.832,
|
| 677 |
+
"grad_norm": 0.10936518013477325,
|
| 678 |
+
"kl": 0.19671630859375,
|
| 679 |
+
"learning_rate": 2.7223302037824845e-06,
|
| 680 |
+
"loss": 0.0079,
|
| 681 |
+
"reward": 1.521875038743019,
|
| 682 |
+
"reward_std": 0.33053973913192747,
|
| 683 |
+
"rewards/accuracy_reward": 0.5567708510905505,
|
| 684 |
+
"rewards/format_reward": 0.9651041850447655,
|
| 685 |
+
"step": 520
|
| 686 |
+
},
|
| 687 |
+
{
|
| 688 |
+
"completion_length": 339.7869876861572,
|
| 689 |
+
"epoch": 0.848,
|
| 690 |
+
"grad_norm": 0.1296410709619522,
|
| 691 |
+
"kl": 0.8387939453125,
|
| 692 |
+
"learning_rate": 2.705928353414784e-06,
|
| 693 |
+
"loss": 0.0335,
|
| 694 |
+
"reward": 1.2877604514360428,
|
| 695 |
+
"reward_std": 0.5975749351084232,
|
| 696 |
+
"rewards/accuracy_reward": 0.4781250134110451,
|
| 697 |
+
"rewards/format_reward": 0.8096354395151139,
|
| 698 |
+
"step": 530
|
| 699 |
+
},
|
| 700 |
+
{
|
| 701 |
+
"completion_length": 333.3028755187988,
|
| 702 |
+
"epoch": 0.864,
|
| 703 |
+
"grad_norm": 0.20703841745853424,
|
| 704 |
+
"kl": 0.3625732421875,
|
| 705 |
+
"learning_rate": 2.6891083083363554e-06,
|
| 706 |
+
"loss": 0.0145,
|
| 707 |
+
"reward": 1.3070312827825545,
|
| 708 |
+
"reward_std": 0.5399560488760471,
|
| 709 |
+
"rewards/accuracy_reward": 0.45468751080334185,
|
| 710 |
+
"rewards/format_reward": 0.8523437708616257,
|
| 711 |
+
"step": 540
|
| 712 |
+
},
|
| 713 |
+
{
|
| 714 |
+
"completion_length": 272.563028717041,
|
| 715 |
+
"epoch": 0.88,
|
| 716 |
+
"grad_norm": 0.16747455298900604,
|
| 717 |
+
"kl": 0.30728759765625,
|
| 718 |
+
"learning_rate": 2.6718759014425513e-06,
|
| 719 |
+
"loss": 0.0123,
|
| 720 |
+
"reward": 1.534114620089531,
|
| 721 |
+
"reward_std": 0.3431927986443043,
|
| 722 |
+
"rewards/accuracy_reward": 0.5791666842997074,
|
| 723 |
+
"rewards/format_reward": 0.9549479365348816,
|
| 724 |
+
"step": 550
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"completion_length": 317.7333419799805,
|
| 728 |
+
"epoch": 0.896,
|
| 729 |
+
"grad_norm": 0.3575699031352997,
|
| 730 |
+
"kl": 0.20316162109375,
|
| 731 |
+
"learning_rate": 2.6542371086285347e-06,
|
| 732 |
+
"loss": 0.0081,
|
| 733 |
+
"reward": 1.5716146260499955,
|
| 734 |
+
"reward_std": 0.3063303453847766,
|
| 735 |
+
"rewards/accuracy_reward": 0.6052083535119891,
|
| 736 |
+
"rewards/format_reward": 0.9664062723517418,
|
| 737 |
+
"step": 560
|
| 738 |
+
},
|
| 739 |
+
{
|
| 740 |
+
"completion_length": 380.475789642334,
|
| 741 |
+
"epoch": 0.912,
|
| 742 |
+
"grad_norm": 0.3914913237094879,
|
| 743 |
+
"kl": 0.68067626953125,
|
| 744 |
+
"learning_rate": 2.6361980467169505e-06,
|
| 745 |
+
"loss": 0.0273,
|
| 746 |
+
"reward": 1.397135455906391,
|
| 747 |
+
"reward_std": 0.4914455428719521,
|
| 748 |
+
"rewards/accuracy_reward": 0.5210937639698386,
|
| 749 |
+
"rewards/format_reward": 0.8760416865348816,
|
| 750 |
+
"step": 570
|
| 751 |
+
},
|
| 752 |
+
{
|
| 753 |
+
"completion_length": 375.67553367614744,
|
| 754 |
+
"epoch": 0.928,
|
| 755 |
+
"grad_norm": 0.31454476714134216,
|
| 756 |
+
"kl": 0.549169921875,
|
| 757 |
+
"learning_rate": 2.6177649713367136e-06,
|
| 758 |
+
"loss": 0.0219,
|
| 759 |
+
"reward": 1.503125038743019,
|
| 760 |
+
"reward_std": 0.5160485468804836,
|
| 761 |
+
"rewards/accuracy_reward": 0.6070312697440385,
|
| 762 |
+
"rewards/format_reward": 0.8960937678813934,
|
| 763 |
+
"step": 580
|
| 764 |
+
},
|
| 765 |
+
{
|
| 766 |
+
"completion_length": 362.68178100585936,
|
| 767 |
+
"epoch": 0.944,
|
| 768 |
+
"grad_norm": 0.08374358713626862,
|
| 769 |
+
"kl": 0.245947265625,
|
| 770 |
+
"learning_rate": 2.5989442747536697e-06,
|
| 771 |
+
"loss": 0.0098,
|
| 772 |
+
"reward": 1.5033854618668556,
|
| 773 |
+
"reward_std": 0.4191708039492369,
|
| 774 |
+
"rewards/accuracy_reward": 0.5708333518356085,
|
| 775 |
+
"rewards/format_reward": 0.9325521036982536,
|
| 776 |
+
"step": 590
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"completion_length": 348.230997467041,
|
| 780 |
+
"epoch": 0.96,
|
| 781 |
+
"grad_norm": 0.08352825045585632,
|
| 782 |
+
"kl": 0.3398193359375,
|
| 783 |
+
"learning_rate": 2.5797424836538714e-06,
|
| 784 |
+
"loss": 0.0136,
|
| 785 |
+
"reward": 1.5054687887430191,
|
| 786 |
+
"reward_std": 0.40789004862308503,
|
| 787 |
+
"rewards/accuracy_reward": 0.5828125124797225,
|
| 788 |
+
"rewards/format_reward": 0.9226562663912773,
|
| 789 |
+
"step": 600
|
| 790 |
+
},
|
| 791 |
+
{
|
| 792 |
+
"completion_length": 348.3810001373291,
|
| 793 |
+
"epoch": 0.976,
|
| 794 |
+
"grad_norm": 0.09684169292449951,
|
| 795 |
+
"kl": 0.5585693359375,
|
| 796 |
+
"learning_rate": 2.560166256880234e-06,
|
| 797 |
+
"loss": 0.0224,
|
| 798 |
+
"reward": 1.5184896290302277,
|
| 799 |
+
"reward_std": 0.4260748438537121,
|
| 800 |
+
"rewards/accuracy_reward": 0.5945312634110451,
|
| 801 |
+
"rewards/format_reward": 0.9239583536982536,
|
| 802 |
+
"step": 610
|
| 803 |
+
},
|
| 804 |
+
{
|
| 805 |
+
"completion_length": 342.1513130187988,
|
| 806 |
+
"epoch": 0.992,
|
| 807 |
+
"grad_norm": 0.0948108583688736,
|
| 808 |
+
"kl": 0.31746826171875,
|
| 809 |
+
"learning_rate": 2.5402223831233723e-06,
|
| 810 |
+
"loss": 0.0127,
|
| 811 |
+
"reward": 1.5098958641290665,
|
| 812 |
+
"reward_std": 0.4502595506608486,
|
| 813 |
+
"rewards/accuracy_reward": 0.5950520992279053,
|
| 814 |
+
"rewards/format_reward": 0.9148437663912773,
|
| 815 |
+
"step": 620
|
| 816 |
+
},
|
| 817 |
+
{
|
| 818 |
+
"completion_length": 360.778133392334,
|
| 819 |
+
"epoch": 1.008,
|
| 820 |
+
"grad_norm": 0.14951100945472717,
|
| 821 |
+
"kl": 0.272119140625,
|
| 822 |
+
"learning_rate": 2.5199177785673957e-06,
|
| 823 |
+
"loss": 0.0109,
|
| 824 |
+
"reward": 1.5187500447034836,
|
| 825 |
+
"reward_std": 0.4504229260608554,
|
| 826 |
+
"rewards/accuracy_reward": 0.6013020960614085,
|
| 827 |
+
"rewards/format_reward": 0.91744794100523,
|
| 828 |
+
"step": 630
|
| 829 |
+
},
|
| 830 |
+
{
|
| 831 |
+
"completion_length": 363.9461048126221,
|
| 832 |
+
"epoch": 1.024,
|
| 833 |
+
"grad_norm": 0.22019609808921814,
|
| 834 |
+
"kl": 0.6080078125,
|
| 835 |
+
"learning_rate": 2.4992594844915022e-06,
|
| 836 |
+
"loss": 0.0243,
|
| 837 |
+
"reward": 1.4822917118668557,
|
| 838 |
+
"reward_std": 0.4976062387228012,
|
| 839 |
+
"rewards/accuracy_reward": 0.5966145992279053,
|
| 840 |
+
"rewards/format_reward": 0.8856771007180214,
|
| 841 |
+
"step": 640
|
| 842 |
+
},
|
| 843 |
+
{
|
| 844 |
+
"completion_length": 303.2153751373291,
|
| 845 |
+
"epoch": 1.04,
|
| 846 |
+
"grad_norm": 0.1117577999830246,
|
| 847 |
+
"kl": 0.28231201171875,
|
| 848 |
+
"learning_rate": 2.4782546648281847e-06,
|
| 849 |
+
"loss": 0.0113,
|
| 850 |
+
"reward": 1.504687535762787,
|
| 851 |
+
"reward_std": 0.3277318266220391,
|
| 852 |
+
"rewards/accuracy_reward": 0.5388020966434851,
|
| 853 |
+
"rewards/format_reward": 0.9658854335546494,
|
| 854 |
+
"step": 650
|
| 855 |
+
},
|
| 856 |
+
{
|
| 857 |
+
"completion_length": 301.4893325805664,
|
| 858 |
+
"epoch": 1.056,
|
| 859 |
+
"grad_norm": 0.09414847195148468,
|
| 860 |
+
"kl": 0.19752197265625,
|
| 861 |
+
"learning_rate": 2.4569106036789064e-06,
|
| 862 |
+
"loss": 0.0079,
|
| 863 |
+
"reward": 1.5304687917232513,
|
| 864 |
+
"reward_std": 0.28476983550935986,
|
| 865 |
+
"rewards/accuracy_reward": 0.5505208492279052,
|
| 866 |
+
"rewards/format_reward": 0.9799479380249977,
|
| 867 |
+
"step": 660
|
| 868 |
+
},
|
| 869 |
+
{
|
| 870 |
+
"completion_length": 380.32605056762696,
|
| 871 |
+
"epoch": 1.072,
|
| 872 |
+
"grad_norm": 0.08695989847183228,
|
| 873 |
+
"kl": 0.3002685546875,
|
| 874 |
+
"learning_rate": 2.4352347027881005e-06,
|
| 875 |
+
"loss": 0.012,
|
| 876 |
+
"reward": 1.4942708730697631,
|
| 877 |
+
"reward_std": 0.4118765268474817,
|
| 878 |
+
"rewards/accuracy_reward": 0.559375013038516,
|
| 879 |
+
"rewards/format_reward": 0.9348958566784858,
|
| 880 |
+
"step": 670
|
| 881 |
+
},
|
| 882 |
+
{
|
| 883 |
+
"completion_length": 362.15209197998047,
|
| 884 |
+
"epoch": 1.088,
|
| 885 |
+
"grad_norm": 0.10074878484010696,
|
| 886 |
+
"kl": 0.3934326171875,
|
| 887 |
+
"learning_rate": 2.413234478976379e-06,
|
| 888 |
+
"loss": 0.0157,
|
| 889 |
+
"reward": 1.5263021305203437,
|
| 890 |
+
"reward_std": 0.3859816137701273,
|
| 891 |
+
"rewards/accuracy_reward": 0.5898437647148966,
|
| 892 |
+
"rewards/format_reward": 0.9364583566784859,
|
| 893 |
+
"step": 680
|
| 894 |
+
},
|
| 895 |
+
{
|
| 896 |
+
"completion_length": 342.3330821990967,
|
| 897 |
+
"epoch": 1.104,
|
| 898 |
+
"grad_norm": 0.11779873073101044,
|
| 899 |
+
"kl": 0.4483154296875,
|
| 900 |
+
"learning_rate": 2.3909175615338297e-06,
|
| 901 |
+
"loss": 0.018,
|
| 902 |
+
"reward": 1.5794271260499955,
|
| 903 |
+
"reward_std": 0.43667961433529856,
|
| 904 |
+
"rewards/accuracy_reward": 0.6510416842997074,
|
| 905 |
+
"rewards/format_reward": 0.9283854380249977,
|
| 906 |
+
"step": 690
|
| 907 |
+
},
|
| 908 |
+
{
|
| 909 |
+
"completion_length": 364.8481903076172,
|
| 910 |
+
"epoch": 1.12,
|
| 911 |
+
"grad_norm": 0.2739701271057129,
|
| 912 |
+
"kl": 0.5840087890625,
|
| 913 |
+
"learning_rate": 2.368291689574312e-06,
|
| 914 |
+
"loss": 0.0233,
|
| 915 |
+
"reward": 1.4492187917232513,
|
| 916 |
+
"reward_std": 0.5059375043958425,
|
| 917 |
+
"rewards/accuracy_reward": 0.5679687663912774,
|
| 918 |
+
"rewards/format_reward": 0.8812500208616256,
|
| 919 |
+
"step": 700
|
| 920 |
+
},
|
| 921 |
+
{
|
| 922 |
+
"completion_length": 299.41016693115233,
|
| 923 |
+
"epoch": 1.1360000000000001,
|
| 924 |
+
"grad_norm": 0.11518736928701401,
|
| 925 |
+
"kl": 0.24130859375,
|
| 926 |
+
"learning_rate": 2.3453647093516705e-06,
|
| 927 |
+
"loss": 0.0096,
|
| 928 |
+
"reward": 1.6536458730697632,
|
| 929 |
+
"reward_std": 0.3213042883202434,
|
| 930 |
+
"rewards/accuracy_reward": 0.6833333440124989,
|
| 931 |
+
"rewards/format_reward": 0.9703125163912774,
|
| 932 |
+
"step": 710
|
| 933 |
+
},
|
| 934 |
+
{
|
| 935 |
+
"completion_length": 322.81980018615724,
|
| 936 |
+
"epoch": 1.152,
|
| 937 |
+
"grad_norm": 0.09168912470340729,
|
| 938 |
+
"kl": 0.46943359375,
|
| 939 |
+
"learning_rate": 2.322144571538792e-06,
|
| 940 |
+
"loss": 0.0188,
|
| 941 |
+
"reward": 1.5898437827825547,
|
| 942 |
+
"reward_std": 0.39194310661405324,
|
| 943 |
+
"rewards/accuracy_reward": 0.6382812660187482,
|
| 944 |
+
"rewards/format_reward": 0.9515625208616256,
|
| 945 |
+
"step": 720
|
| 946 |
+
},
|
| 947 |
+
{
|
| 948 |
+
"completion_length": 383.13386459350585,
|
| 949 |
+
"epoch": 1.168,
|
| 950 |
+
"grad_norm": 0.2942081093788147,
|
| 951 |
+
"kl": 0.3664794921875,
|
| 952 |
+
"learning_rate": 2.2986393284704496e-06,
|
| 953 |
+
"loss": 0.0147,
|
| 954 |
+
"reward": 1.4242187917232514,
|
| 955 |
+
"reward_std": 0.519075758382678,
|
| 956 |
+
"rewards/accuracy_reward": 0.5468750189524144,
|
| 957 |
+
"rewards/format_reward": 0.8773437738418579,
|
| 958 |
+
"step": 730
|
| 959 |
+
},
|
| 960 |
+
{
|
| 961 |
+
"completion_length": 323.92474937438965,
|
| 962 |
+
"epoch": 1.184,
|
| 963 |
+
"grad_norm": 0.7609843015670776,
|
| 964 |
+
"kl": 0.9059814453125,
|
| 965 |
+
"learning_rate": 2.2748571313509e-06,
|
| 966 |
+
"loss": 0.0363,
|
| 967 |
+
"reward": 1.4992187842726707,
|
| 968 |
+
"reward_std": 0.4844189383089542,
|
| 969 |
+
"rewards/accuracy_reward": 0.5958333497866988,
|
| 970 |
+
"rewards/format_reward": 0.9033854320645333,
|
| 971 |
+
"step": 740
|
| 972 |
+
},
|
| 973 |
+
{
|
| 974 |
+
"completion_length": 312.4018325805664,
|
| 975 |
+
"epoch": 1.2,
|
| 976 |
+
"grad_norm": 0.26806285977363586,
|
| 977 |
+
"kl": 0.352099609375,
|
| 978 |
+
"learning_rate": 2.2508062274271832e-06,
|
| 979 |
+
"loss": 0.0141,
|
| 980 |
+
"reward": 1.5622396349906922,
|
| 981 |
+
"reward_std": 0.3421931225806475,
|
| 982 |
+
"rewards/accuracy_reward": 0.6031250144354999,
|
| 983 |
+
"rewards/format_reward": 0.959114608168602,
|
| 984 |
+
"step": 750
|
| 985 |
+
},
|
| 986 |
+
{
|
| 987 |
+
"completion_length": 371.5671989440918,
|
| 988 |
+
"epoch": 1.216,
|
| 989 |
+
"grad_norm": 0.09768559783697128,
|
| 990 |
+
"kl": 0.418310546875,
|
| 991 |
+
"learning_rate": 2.2264949571291272e-06,
|
| 992 |
+
"loss": 0.0167,
|
| 993 |
+
"reward": 1.5015625447034835,
|
| 994 |
+
"reward_std": 0.4462232066318393,
|
| 995 |
+
"rewards/accuracy_reward": 0.5955729261040688,
|
| 996 |
+
"rewards/format_reward": 0.9059896036982537,
|
| 997 |
+
"step": 760
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"completion_length": 357.2544361114502,
|
| 1001 |
+
"epoch": 1.232,
|
| 1002 |
+
"grad_norm": 1.3492963314056396,
|
| 1003 |
+
"kl": 0.36956787109375,
|
| 1004 |
+
"learning_rate": 2.2019317511770334e-06,
|
| 1005 |
+
"loss": 0.0148,
|
| 1006 |
+
"reward": 1.5296875447034837,
|
| 1007 |
+
"reward_std": 0.38438957259058953,
|
| 1008 |
+
"rewards/accuracy_reward": 0.5861979339271783,
|
| 1009 |
+
"rewards/format_reward": 0.943489608168602,
|
| 1010 |
+
"step": 770
|
| 1011 |
+
},
|
| 1012 |
+
{
|
| 1013 |
+
"completion_length": 324.1862083435059,
|
| 1014 |
+
"epoch": 1.248,
|
| 1015 |
+
"grad_norm": 0.0821109488606453,
|
| 1016 |
+
"kl": 0.37724609375,
|
| 1017 |
+
"learning_rate": 2.1771251276580473e-06,
|
| 1018 |
+
"loss": 0.0151,
|
| 1019 |
+
"reward": 1.563802120089531,
|
| 1020 |
+
"reward_std": 0.38602438326925037,
|
| 1021 |
+
"rewards/accuracy_reward": 0.6151041872799397,
|
| 1022 |
+
"rewards/format_reward": 0.9486979365348815,
|
| 1023 |
+
"step": 780
|
| 1024 |
+
},
|
| 1025 |
+
{
|
| 1026 |
+
"completion_length": 343.0974063873291,
|
| 1027 |
+
"epoch": 1.264,
|
| 1028 |
+
"grad_norm": 0.11053454130887985,
|
| 1029 |
+
"kl": 0.3335693359375,
|
| 1030 |
+
"learning_rate": 2.152083689072242e-06,
|
| 1031 |
+
"loss": 0.0134,
|
| 1032 |
+
"reward": 1.500260454416275,
|
| 1033 |
+
"reward_std": 0.45653478614985943,
|
| 1034 |
+
"rewards/accuracy_reward": 0.5726562667638063,
|
| 1035 |
+
"rewards/format_reward": 0.92760419100523,
|
| 1036 |
+
"step": 790
|
| 1037 |
+
},
|
| 1038 |
+
{
|
| 1039 |
+
"completion_length": 333.49376106262207,
|
| 1040 |
+
"epoch": 1.28,
|
| 1041 |
+
"grad_norm": 0.09054333716630936,
|
| 1042 |
+
"kl": 0.4177734375,
|
| 1043 |
+
"learning_rate": 2.126816119349417e-06,
|
| 1044 |
+
"loss": 0.0167,
|
| 1045 |
+
"reward": 1.53333338201046,
|
| 1046 |
+
"reward_std": 0.4124399437569082,
|
| 1047 |
+
"rewards/accuracy_reward": 0.5903645984828472,
|
| 1048 |
+
"rewards/format_reward": 0.9429687693715095,
|
| 1049 |
+
"step": 800
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"completion_length": 309.3979267120361,
|
| 1053 |
+
"epoch": 1.296,
|
| 1054 |
+
"grad_norm": 0.1404261738061905,
|
| 1055 |
+
"kl": 0.30087890625,
|
| 1056 |
+
"learning_rate": 2.1013311808376683e-06,
|
| 1057 |
+
"loss": 0.012,
|
| 1058 |
+
"reward": 1.5450521230697631,
|
| 1059 |
+
"reward_std": 0.3885490225628018,
|
| 1060 |
+
"rewards/accuracy_reward": 0.5989583499729634,
|
| 1061 |
+
"rewards/format_reward": 0.9460937708616257,
|
| 1062 |
+
"step": 810
|
| 1063 |
+
},
|
| 1064 |
+
{
|
| 1065 |
+
"completion_length": 355.4174579620361,
|
| 1066 |
+
"epoch": 1.312,
|
| 1067 |
+
"grad_norm": 0.21735621988773346,
|
| 1068 |
+
"kl": 396.079345703125,
|
| 1069 |
+
"learning_rate": 2.075637711264759e-06,
|
| 1070 |
+
"loss": 15.8661,
|
| 1071 |
+
"reward": 1.4781250327825546,
|
| 1072 |
+
"reward_std": 0.475801320374012,
|
| 1073 |
+
"rewards/accuracy_reward": 0.5750000145286321,
|
| 1074 |
+
"rewards/format_reward": 0.9031250223517417,
|
| 1075 |
+
"step": 820
|
| 1076 |
+
},
|
| 1077 |
+
{
|
| 1078 |
+
"completion_length": 340.7921970367432,
|
| 1079 |
+
"epoch": 1.328,
|
| 1080 |
+
"grad_norm": 0.41135042905807495,
|
| 1081 |
+
"kl": 0.43037109375,
|
| 1082 |
+
"learning_rate": 2.04974462067335e-06,
|
| 1083 |
+
"loss": 0.0172,
|
| 1084 |
+
"reward": 1.5763021230697631,
|
| 1085 |
+
"reward_std": 0.45917638950049877,
|
| 1086 |
+
"rewards/accuracy_reward": 0.6552083536982536,
|
| 1087 |
+
"rewards/format_reward": 0.9210937678813934,
|
| 1088 |
+
"step": 830
|
| 1089 |
+
},
|
| 1090 |
+
{
|
| 1091 |
+
"completion_length": 345.1257911682129,
|
| 1092 |
+
"epoch": 1.3439999999999999,
|
| 1093 |
+
"grad_norm": 0.11835141479969025,
|
| 1094 |
+
"kl": 0.3072998046875,
|
| 1095 |
+
"learning_rate": 2.023660888331156e-06,
|
| 1096 |
+
"loss": 0.0123,
|
| 1097 |
+
"reward": 1.5898437917232513,
|
| 1098 |
+
"reward_std": 0.41639630161225794,
|
| 1099 |
+
"rewards/accuracy_reward": 0.6492187671363354,
|
| 1100 |
+
"rewards/format_reward": 0.9406250193715096,
|
| 1101 |
+
"step": 840
|
| 1102 |
+
},
|
| 1103 |
+
{
|
| 1104 |
+
"completion_length": 314.01824111938475,
|
| 1105 |
+
"epoch": 1.3599999999999999,
|
| 1106 |
+
"grad_norm": 0.11381607502698898,
|
| 1107 |
+
"kl": 0.320751953125,
|
| 1108 |
+
"learning_rate": 1.997395559617093e-06,
|
| 1109 |
+
"loss": 0.0128,
|
| 1110 |
+
"reward": 1.594791704416275,
|
| 1111 |
+
"reward_std": 0.34149147048592565,
|
| 1112 |
+
"rewards/accuracy_reward": 0.6294271037913859,
|
| 1113 |
+
"rewards/format_reward": 0.9653646007180214,
|
| 1114 |
+
"step": 850
|
| 1115 |
+
},
|
| 1116 |
+
{
|
| 1117 |
+
"completion_length": 324.5421962738037,
|
| 1118 |
+
"epoch": 1.376,
|
| 1119 |
+
"grad_norm": 0.23615330457687378,
|
| 1120 |
+
"kl": 0.45950927734375,
|
| 1121 |
+
"learning_rate": 1.9709577428844986e-06,
|
| 1122 |
+
"loss": 0.0184,
|
| 1123 |
+
"reward": 1.5335937917232514,
|
| 1124 |
+
"reward_std": 0.38021210972219704,
|
| 1125 |
+
"rewards/accuracy_reward": 0.5817708492279052,
|
| 1126 |
+
"rewards/format_reward": 0.9518229350447655,
|
| 1127 |
+
"step": 860
|
| 1128 |
+
},
|
| 1129 |
+
{
|
| 1130 |
+
"completion_length": 347.88047943115237,
|
| 1131 |
+
"epoch": 1.392,
|
| 1132 |
+
"grad_norm": 0.09267138689756393,
|
| 1133 |
+
"kl": 0.2773193359375,
|
| 1134 |
+
"learning_rate": 1.9443566063025173e-06,
|
| 1135 |
+
"loss": 0.0111,
|
| 1136 |
+
"reward": 1.4914062932133674,
|
| 1137 |
+
"reward_std": 0.4475890576839447,
|
| 1138 |
+
"rewards/accuracy_reward": 0.5679687656462192,
|
| 1139 |
+
"rewards/format_reward": 0.9234375193715095,
|
| 1140 |
+
"step": 870
|
| 1141 |
+
},
|
| 1142 |
+
{
|
| 1143 |
+
"completion_length": 324.02969856262206,
|
| 1144 |
+
"epoch": 1.408,
|
| 1145 |
+
"grad_norm": 0.08601139485836029,
|
| 1146 |
+
"kl": 0.30263671875,
|
| 1147 |
+
"learning_rate": 1.9176013746767422e-06,
|
| 1148 |
+
"loss": 0.0121,
|
| 1149 |
+
"reward": 1.6111979484558105,
|
| 1150 |
+
"reward_std": 0.40976997539401055,
|
| 1151 |
+
"rewards/accuracy_reward": 0.665104179084301,
|
| 1152 |
+
"rewards/format_reward": 0.9460937723517417,
|
| 1153 |
+
"step": 880
|
| 1154 |
+
},
|
| 1155 |
+
{
|
| 1156 |
+
"completion_length": 313.2916774749756,
|
| 1157 |
+
"epoch": 1.424,
|
| 1158 |
+
"grad_norm": 0.09291204810142517,
|
| 1159 |
+
"kl": 0.31865234375,
|
| 1160 |
+
"learning_rate": 1.8907013262502107e-06,
|
| 1161 |
+
"loss": 0.0127,
|
| 1162 |
+
"reward": 1.5414062976837157,
|
| 1163 |
+
"reward_std": 0.38301597684621813,
|
| 1164 |
+
"rewards/accuracy_reward": 0.5854166820645332,
|
| 1165 |
+
"rewards/format_reward": 0.9559895992279053,
|
| 1166 |
+
"step": 890
|
| 1167 |
+
},
|
| 1168 |
+
{
|
| 1169 |
+
"completion_length": 341.86511344909667,
|
| 1170 |
+
"epoch": 1.44,
|
| 1171 |
+
"grad_norm": 0.08695019036531448,
|
| 1172 |
+
"kl": 0.4276123046875,
|
| 1173 |
+
"learning_rate": 1.8636657894858784e-06,
|
| 1174 |
+
"loss": 0.0171,
|
| 1175 |
+
"reward": 1.5312500506639481,
|
| 1176 |
+
"reward_std": 0.3857471447438002,
|
| 1177 |
+
"rewards/accuracy_reward": 0.593750013038516,
|
| 1178 |
+
"rewards/format_reward": 0.9375000178813935,
|
| 1179 |
+
"step": 900
|
| 1180 |
+
},
|
| 1181 |
+
{
|
| 1182 |
+
"completion_length": 328.9026153564453,
|
| 1183 |
+
"epoch": 1.456,
|
| 1184 |
+
"grad_norm": 0.1095338836312294,
|
| 1185 |
+
"kl": 1.388330078125,
|
| 1186 |
+
"learning_rate": 1.8365041398316678e-06,
|
| 1187 |
+
"loss": 0.0556,
|
| 1188 |
+
"reward": 1.488802120089531,
|
| 1189 |
+
"reward_std": 0.4116742081940174,
|
| 1190 |
+
"rewards/accuracy_reward": 0.5505208489485085,
|
| 1191 |
+
"rewards/format_reward": 0.9382812678813934,
|
| 1192 |
+
"step": 910
|
| 1193 |
+
},
|
| 1194 |
+
{
|
| 1195 |
+
"completion_length": 348.82787590026857,
|
| 1196 |
+
"epoch": 1.472,
|
| 1197 |
+
"grad_norm": 0.12603142857551575,
|
| 1198 |
+
"kl": 0.378857421875,
|
| 1199 |
+
"learning_rate": 1.8092257964692304e-06,
|
| 1200 |
+
"loss": 0.0152,
|
| 1201 |
+
"reward": 1.4481771260499954,
|
| 1202 |
+
"reward_std": 0.49320419803261756,
|
| 1203 |
+
"rewards/accuracy_reward": 0.545833345502615,
|
| 1204 |
+
"rewards/format_reward": 0.9023437693715095,
|
| 1205 |
+
"step": 920
|
| 1206 |
+
},
|
| 1207 |
+
{
|
| 1208 |
+
"completion_length": 336.4057384490967,
|
| 1209 |
+
"epoch": 1.488,
|
| 1210 |
+
"grad_norm": 0.06563200801610947,
|
| 1211 |
+
"kl": 0.296435546875,
|
| 1212 |
+
"learning_rate": 1.781840219047541e-06,
|
| 1213 |
+
"loss": 0.0119,
|
| 1214 |
+
"reward": 1.5815104573965073,
|
| 1215 |
+
"reward_std": 0.4233523942530155,
|
| 1216 |
+
"rewards/accuracy_reward": 0.6494791835546494,
|
| 1217 |
+
"rewards/format_reward": 0.9320312693715096,
|
| 1218 |
+
"step": 930
|
| 1219 |
+
},
|
| 1220 |
+
{
|
| 1221 |
+
"completion_length": 389.78751373291016,
|
| 1222 |
+
"epoch": 1.504,
|
| 1223 |
+
"grad_norm": 0.13051985204219818,
|
| 1224 |
+
"kl": 0.4625,
|
| 1225 |
+
"learning_rate": 1.7543569044024565e-06,
|
| 1226 |
+
"loss": 0.0185,
|
| 1227 |
+
"reward": 1.4177083730697633,
|
| 1228 |
+
"reward_std": 0.5342824589461088,
|
| 1229 |
+
"rewards/accuracy_reward": 0.5640625163912774,
|
| 1230 |
+
"rewards/format_reward": 0.8536458507180213,
|
| 1231 |
+
"step": 940
|
| 1232 |
+
},
|
| 1233 |
+
{
|
| 1234 |
+
"completion_length": 309.4536560058594,
|
| 1235 |
+
"epoch": 1.52,
|
| 1236 |
+
"grad_norm": 0.2592553496360779,
|
| 1237 |
+
"kl": 0.3264892578125,
|
| 1238 |
+
"learning_rate": 1.7267853832633819e-06,
|
| 1239 |
+
"loss": 0.0131,
|
| 1240 |
+
"reward": 1.510416704416275,
|
| 1241 |
+
"reward_std": 0.4337383009493351,
|
| 1242 |
+
"rewards/accuracy_reward": 0.594010425824672,
|
| 1243 |
+
"rewards/format_reward": 0.9164062738418579,
|
| 1244 |
+
"step": 950
|
| 1245 |
+
},
|
| 1246 |
+
{
|
| 1247 |
+
"completion_length": 287.96485176086424,
|
| 1248 |
+
"epoch": 1.536,
|
| 1249 |
+
"grad_norm": 0.1538826823234558,
|
| 1250 |
+
"kl": 0.4028076171875,
|
| 1251 |
+
"learning_rate": 1.6991352169481808e-06,
|
| 1252 |
+
"loss": 0.0161,
|
| 1253 |
+
"reward": 1.5739583730697633,
|
| 1254 |
+
"reward_std": 0.3966914664953947,
|
| 1255 |
+
"rewards/accuracy_reward": 0.6291666841134429,
|
| 1256 |
+
"rewards/format_reward": 0.9447916880249977,
|
| 1257 |
+
"step": 960
|
| 1258 |
+
},
|
| 1259 |
+
{
|
| 1260 |
+
"completion_length": 341.0164161682129,
|
| 1261 |
+
"epoch": 1.552,
|
| 1262 |
+
"grad_norm": 0.18513712286949158,
|
| 1263 |
+
"kl": 0.560888671875,
|
| 1264 |
+
"learning_rate": 1.6714159940474768e-06,
|
| 1265 |
+
"loss": 0.0224,
|
| 1266 |
+
"reward": 1.5395833611488343,
|
| 1267 |
+
"reward_std": 0.4434517964720726,
|
| 1268 |
+
"rewards/accuracy_reward": 0.6177083533257246,
|
| 1269 |
+
"rewards/format_reward": 0.9218750253319741,
|
| 1270 |
+
"step": 970
|
| 1271 |
+
},
|
| 1272 |
+
{
|
| 1273 |
+
"completion_length": 350.5575626373291,
|
| 1274 |
+
"epoch": 1.568,
|
| 1275 |
+
"grad_norm": 0.07839391380548477,
|
| 1276 |
+
"kl": 0.440478515625,
|
| 1277 |
+
"learning_rate": 1.6436373270995033e-06,
|
| 1278 |
+
"loss": 0.0176,
|
| 1279 |
+
"reward": 1.5424479573965073,
|
| 1280 |
+
"reward_std": 0.4582442186772823,
|
| 1281 |
+
"rewards/accuracy_reward": 0.6197916835546493,
|
| 1282 |
+
"rewards/format_reward": 0.9226562708616257,
|
| 1283 |
+
"step": 980
|
| 1284 |
+
},
|
| 1285 |
+
{
|
| 1286 |
+
"completion_length": 336.3362071990967,
|
| 1287 |
+
"epoch": 1.584,
|
| 1288 |
+
"grad_norm": 0.11262823641300201,
|
| 1289 |
+
"kl": 0.4291748046875,
|
| 1290 |
+
"learning_rate": 1.61580884925664e-06,
|
| 1291 |
+
"loss": 0.0172,
|
| 1292 |
+
"reward": 1.5526042044162751,
|
| 1293 |
+
"reward_std": 0.44057157076895237,
|
| 1294 |
+
"rewards/accuracy_reward": 0.6263021004851907,
|
| 1295 |
+
"rewards/format_reward": 0.9263021007180214,
|
| 1296 |
+
"step": 990
|
| 1297 |
+
},
|
| 1298 |
+
{
|
| 1299 |
+
"completion_length": 385.09662437438965,
|
| 1300 |
+
"epoch": 1.6,
|
| 1301 |
+
"grad_norm": 0.09378820657730103,
|
| 1302 |
+
"kl": 40.2127197265625,
|
| 1303 |
+
"learning_rate": 1.5879402109448092e-06,
|
| 1304 |
+
"loss": 1.6059,
|
| 1305 |
+
"reward": 1.472916704416275,
|
| 1306 |
+
"reward_std": 0.49806156009435654,
|
| 1307 |
+
"rewards/accuracy_reward": 0.5927083514630794,
|
| 1308 |
+
"rewards/format_reward": 0.8802083507180214,
|
| 1309 |
+
"step": 1000
|
| 1310 |
+
},
|
| 1311 |
+
{
|
| 1312 |
+
"completion_length": 320.54193649291994,
|
| 1313 |
+
"epoch": 1.616,
|
| 1314 |
+
"grad_norm": 0.19597963988780975,
|
| 1315 |
+
"kl": 0.37021484375,
|
| 1316 |
+
"learning_rate": 1.5600410765168756e-06,
|
| 1317 |
+
"loss": 0.0148,
|
| 1318 |
+
"reward": 1.566406288743019,
|
| 1319 |
+
"reward_std": 0.39799929689615965,
|
| 1320 |
+
"rewards/accuracy_reward": 0.6265625130385161,
|
| 1321 |
+
"rewards/format_reward": 0.9398437708616256,
|
| 1322 |
+
"step": 1010
|
| 1323 |
+
},
|
| 1324 |
+
{
|
| 1325 |
+
"completion_length": 274.95834197998045,
|
| 1326 |
+
"epoch": 1.6320000000000001,
|
| 1327 |
+
"grad_norm": 0.10498908162117004,
|
| 1328 |
+
"kl": 1.54697265625,
|
| 1329 |
+
"learning_rate": 1.53212112090122e-06,
|
| 1330 |
+
"loss": 0.0618,
|
| 1331 |
+
"reward": 1.6328125432133676,
|
| 1332 |
+
"reward_std": 0.311348158121109,
|
| 1333 |
+
"rewards/accuracy_reward": 0.6619791840668767,
|
| 1334 |
+
"rewards/format_reward": 0.9708333551883698,
|
| 1335 |
+
"step": 1020
|
| 1336 |
+
},
|
| 1337 |
+
{
|
| 1338 |
+
"completion_length": 319.71302909851073,
|
| 1339 |
+
"epoch": 1.6480000000000001,
|
| 1340 |
+
"grad_norm": 0.09473922103643417,
|
| 1341 |
+
"kl": 0.5324951171875,
|
| 1342 |
+
"learning_rate": 1.5041900262466447e-06,
|
| 1343 |
+
"loss": 0.0213,
|
| 1344 |
+
"reward": 1.5330729544162751,
|
| 1345 |
+
"reward_std": 0.32746845642104744,
|
| 1346 |
+
"rewards/accuracy_reward": 0.5736979268491268,
|
| 1347 |
+
"rewards/format_reward": 0.9593750178813935,
|
| 1348 |
+
"step": 1030
|
| 1349 |
+
},
|
| 1350 |
+
{
|
| 1351 |
+
"completion_length": 355.3851661682129,
|
| 1352 |
+
"epoch": 1.6640000000000001,
|
| 1353 |
+
"grad_norm": 0.0937461331486702,
|
| 1354 |
+
"kl": 0.4345703125,
|
| 1355 |
+
"learning_rate": 1.4762574785647733e-06,
|
| 1356 |
+
"loss": 0.0174,
|
| 1357 |
+
"reward": 1.4458333671092987,
|
| 1358 |
+
"reward_std": 0.46327271312475204,
|
| 1359 |
+
"rewards/accuracy_reward": 0.5424479328095912,
|
| 1360 |
+
"rewards/format_reward": 0.9033854380249977,
|
| 1361 |
+
"step": 1040
|
| 1362 |
+
},
|
| 1363 |
+
{
|
| 1364 |
+
"completion_length": 351.1898559570312,
|
| 1365 |
+
"epoch": 1.6800000000000002,
|
| 1366 |
+
"grad_norm": 0.0828389897942543,
|
| 1367 |
+
"kl": 0.48388671875,
|
| 1368 |
+
"learning_rate": 1.448333164371115e-06,
|
| 1369 |
+
"loss": 0.0194,
|
| 1370 |
+
"reward": 1.484895871579647,
|
| 1371 |
+
"reward_std": 0.47403750047087667,
|
| 1372 |
+
"rewards/accuracy_reward": 0.5729166816920042,
|
| 1373 |
+
"rewards/format_reward": 0.91197919100523,
|
| 1374 |
+
"step": 1050
|
| 1375 |
+
},
|
| 1376 |
+
{
|
| 1377 |
+
"completion_length": 354.74141693115234,
|
| 1378 |
+
"epoch": 1.696,
|
| 1379 |
+
"grad_norm": 0.168987438082695,
|
| 1380 |
+
"kl": 0.7384521484375,
|
| 1381 |
+
"learning_rate": 1.4204267673259495e-06,
|
| 1382 |
+
"loss": 0.0295,
|
| 1383 |
+
"reward": 1.4638021171092988,
|
| 1384 |
+
"reward_std": 0.5317467883229255,
|
| 1385 |
+
"rewards/accuracy_reward": 0.5744791775941849,
|
| 1386 |
+
"rewards/format_reward": 0.8893229335546493,
|
| 1387 |
+
"step": 1060
|
| 1388 |
+
},
|
| 1389 |
+
{
|
| 1390 |
+
"completion_length": 304.412247467041,
|
| 1391 |
+
"epoch": 1.712,
|
| 1392 |
+
"grad_norm": 5.448803901672363,
|
| 1393 |
+
"kl": 0.60498046875,
|
| 1394 |
+
"learning_rate": 1.3925479648762055e-06,
|
| 1395 |
+
"loss": 0.0242,
|
| 1396 |
+
"reward": 1.3429687917232513,
|
| 1397 |
+
"reward_std": 0.5209484387189149,
|
| 1398 |
+
"rewards/accuracy_reward": 0.45364584792405366,
|
| 1399 |
+
"rewards/format_reward": 0.8893229365348816,
|
| 1400 |
+
"step": 1070
|
| 1401 |
+
},
|
| 1402 |
+
{
|
| 1403 |
+
"completion_length": 412.5049598693848,
|
| 1404 |
+
"epoch": 1.728,
|
| 1405 |
+
"grad_norm": 0.12441123276948929,
|
| 1406 |
+
"kl": 0.9303955078125,
|
| 1407 |
+
"learning_rate": 1.364706424899492e-06,
|
| 1408 |
+
"loss": 0.0372,
|
| 1409 |
+
"reward": 1.1434896126389504,
|
| 1410 |
+
"reward_std": 0.6584706656634808,
|
| 1411 |
+
"rewards/accuracy_reward": 0.40442709531635046,
|
| 1412 |
+
"rewards/format_reward": 0.7390625201165676,
|
| 1413 |
+
"step": 1080
|
| 1414 |
+
},
|
| 1415 |
+
{
|
| 1416 |
+
"completion_length": 301.4174571990967,
|
| 1417 |
+
"epoch": 1.744,
|
| 1418 |
+
"grad_norm": 0.2378871887922287,
|
| 1419 |
+
"kl": 0.33017578125,
|
| 1420 |
+
"learning_rate": 1.3369118023514485e-06,
|
| 1421 |
+
"loss": 0.0132,
|
| 1422 |
+
"reward": 1.4455729559063912,
|
| 1423 |
+
"reward_std": 0.4887973885983229,
|
| 1424 |
+
"rewards/accuracy_reward": 0.533854181971401,
|
| 1425 |
+
"rewards/format_reward": 0.9117187678813934,
|
| 1426 |
+
"step": 1090
|
| 1427 |
+
},
|
| 1428 |
+
{
|
| 1429 |
+
"completion_length": 302.38151969909666,
|
| 1430 |
+
"epoch": 1.76,
|
| 1431 |
+
"grad_norm": 0.15944868326187134,
|
| 1432 |
+
"kl": 0.4225830078125,
|
| 1433 |
+
"learning_rate": 1.3091737359175766e-06,
|
| 1434 |
+
"loss": 0.0169,
|
| 1435 |
+
"reward": 1.437239620089531,
|
| 1436 |
+
"reward_std": 0.5037642396986485,
|
| 1437 |
+
"rewards/accuracy_reward": 0.5348958517191932,
|
| 1438 |
+
"rewards/format_reward": 0.9023437738418579,
|
| 1439 |
+
"step": 1100
|
| 1440 |
+
},
|
| 1441 |
+
{
|
| 1442 |
+
"completion_length": 448.40626373291013,
|
| 1443 |
+
"epoch": 1.776,
|
| 1444 |
+
"grad_norm": 0.2753123342990875,
|
| 1445 |
+
"kl": 0.99765625,
|
| 1446 |
+
"learning_rate": 1.2815018446707142e-06,
|
| 1447 |
+
"loss": 0.0399,
|
| 1448 |
+
"reward": 1.141927120089531,
|
| 1449 |
+
"reward_std": 0.6968318119645118,
|
| 1450 |
+
"rewards/accuracy_reward": 0.4669270968064666,
|
| 1451 |
+
"rewards/format_reward": 0.6750000223517418,
|
| 1452 |
+
"step": 1110
|
| 1453 |
+
},
|
| 1454 |
+
{
|
| 1455 |
+
"completion_length": 335.4994888305664,
|
| 1456 |
+
"epoch": 1.792,
|
| 1457 |
+
"grad_norm": 0.13646121323108673,
|
| 1458 |
+
"kl": 0.5754638671875,
|
| 1459 |
+
"learning_rate": 1.253905724735309e-06,
|
| 1460 |
+
"loss": 0.023,
|
| 1461 |
+
"reward": 1.4078125417232514,
|
| 1462 |
+
"reward_std": 0.550966077670455,
|
| 1463 |
+
"rewards/accuracy_reward": 0.5497395996004343,
|
| 1464 |
+
"rewards/format_reward": 0.8580729365348816,
|
| 1465 |
+
"step": 1120
|
| 1466 |
+
},
|
| 1467 |
+
{
|
| 1468 |
+
"completion_length": 287.5849044799805,
|
| 1469 |
+
"epoch": 1.808,
|
| 1470 |
+
"grad_norm": 0.116419717669487,
|
| 1471 |
+
"kl": 0.38251953125,
|
| 1472 |
+
"learning_rate": 1.2263949459596545e-06,
|
| 1473 |
+
"loss": 0.0153,
|
| 1474 |
+
"reward": 1.5557292193174361,
|
| 1475 |
+
"reward_std": 0.370727850869298,
|
| 1476 |
+
"rewards/accuracy_reward": 0.600781269185245,
|
| 1477 |
+
"rewards/format_reward": 0.9549479365348816,
|
| 1478 |
+
"step": 1130
|
| 1479 |
+
},
|
| 1480 |
+
{
|
| 1481 |
+
"completion_length": 267.22839508056643,
|
| 1482 |
+
"epoch": 1.8239999999999998,
|
| 1483 |
+
"grad_norm": 0.22047029435634613,
|
| 1484 |
+
"kl": 0.32794189453125,
|
| 1485 |
+
"learning_rate": 1.1989790485972312e-06,
|
| 1486 |
+
"loss": 0.0131,
|
| 1487 |
+
"reward": 1.5026041999459268,
|
| 1488 |
+
"reward_std": 0.3551323272287846,
|
| 1489 |
+
"rewards/accuracy_reward": 0.5403646015096456,
|
| 1490 |
+
"rewards/format_reward": 0.9622396036982537,
|
| 1491 |
+
"step": 1140
|
| 1492 |
+
},
|
| 1493 |
+
{
|
| 1494 |
+
"completion_length": 308.1588619232178,
|
| 1495 |
+
"epoch": 1.8399999999999999,
|
| 1496 |
+
"grad_norm": 0.3132161498069763,
|
| 1497 |
+
"kl": 0.46527099609375,
|
| 1498 |
+
"learning_rate": 1.171667539998318e-06,
|
| 1499 |
+
"loss": 0.0186,
|
| 1500 |
+
"reward": 1.5867187917232513,
|
| 1501 |
+
"reward_std": 0.36549231559038164,
|
| 1502 |
+
"rewards/accuracy_reward": 0.6335937686264514,
|
| 1503 |
+
"rewards/format_reward": 0.9531250223517418,
|
| 1504 |
+
"step": 1150
|
| 1505 |
+
},
|
| 1506 |
+
{
|
| 1507 |
+
"completion_length": 339.93542861938477,
|
| 1508 |
+
"epoch": 1.8559999999999999,
|
| 1509 |
+
"grad_norm": 0.10203922539949417,
|
| 1510 |
+
"kl": 0.5742431640625,
|
| 1511 |
+
"learning_rate": 1.1444698913130093e-06,
|
| 1512 |
+
"loss": 0.023,
|
| 1513 |
+
"reward": 1.501041704416275,
|
| 1514 |
+
"reward_std": 0.48126591108739375,
|
| 1515 |
+
"rewards/accuracy_reward": 0.5880208533257246,
|
| 1516 |
+
"rewards/format_reward": 0.9130208522081376,
|
| 1517 |
+
"step": 1160
|
| 1518 |
+
},
|
| 1519 |
+
{
|
| 1520 |
+
"completion_length": 402.17761306762696,
|
| 1521 |
+
"epoch": 1.8719999999999999,
|
| 1522 |
+
"grad_norm": 0.10859699547290802,
|
| 1523 |
+
"kl": 0.718212890625,
|
| 1524 |
+
"learning_rate": 1.1173955342067857e-06,
|
| 1525 |
+
"loss": 0.0287,
|
| 1526 |
+
"reward": 1.335677121579647,
|
| 1527 |
+
"reward_std": 0.6192147806286812,
|
| 1528 |
+
"rewards/accuracy_reward": 0.5356770996004343,
|
| 1529 |
+
"rewards/format_reward": 0.8000000193715096,
|
| 1530 |
+
"step": 1170
|
| 1531 |
+
},
|
| 1532 |
+
{
|
| 1533 |
+
"completion_length": 330.6448013305664,
|
| 1534 |
+
"epoch": 1.888,
|
| 1535 |
+
"grad_norm": 0.09255196154117584,
|
| 1536 |
+
"kl": 0.36551513671875,
|
| 1537 |
+
"learning_rate": 1.090453857589783e-06,
|
| 1538 |
+
"loss": 0.0146,
|
| 1539 |
+
"reward": 1.5846354484558105,
|
| 1540 |
+
"reward_std": 0.43822822347283363,
|
| 1541 |
+
"rewards/accuracy_reward": 0.6536458495538682,
|
| 1542 |
+
"rewards/format_reward": 0.9309895977377891,
|
| 1543 |
+
"step": 1180
|
| 1544 |
+
},
|
| 1545 |
+
{
|
| 1546 |
+
"completion_length": 307.15391540527344,
|
| 1547 |
+
"epoch": 1.904,
|
| 1548 |
+
"grad_norm": 0.10617883503437042,
|
| 1549 |
+
"kl": 0.38302001953125,
|
| 1550 |
+
"learning_rate": 1.0636542043608775e-06,
|
| 1551 |
+
"loss": 0.0153,
|
| 1552 |
+
"reward": 1.607552121579647,
|
| 1553 |
+
"reward_std": 0.38010403923690317,
|
| 1554 |
+
"rewards/accuracy_reward": 0.6497395992279053,
|
| 1555 |
+
"rewards/format_reward": 0.9578125238418579,
|
| 1556 |
+
"step": 1190
|
| 1557 |
+
},
|
| 1558 |
+
{
|
| 1559 |
+
"completion_length": 332.0044364929199,
|
| 1560 |
+
"epoch": 1.92,
|
| 1561 |
+
"grad_norm": 0.22778630256652832,
|
| 1562 |
+
"kl": 0.4427490234375,
|
| 1563 |
+
"learning_rate": 1.0370058681677376e-06,
|
| 1564 |
+
"loss": 0.0177,
|
| 1565 |
+
"reward": 1.5015625342726708,
|
| 1566 |
+
"reward_std": 0.42089375481009483,
|
| 1567 |
+
"rewards/accuracy_reward": 0.5770833486691117,
|
| 1568 |
+
"rewards/format_reward": 0.9244791865348816,
|
| 1569 |
+
"step": 1200
|
| 1570 |
+
},
|
| 1571 |
+
{
|
| 1572 |
+
"completion_length": 315.778914642334,
|
| 1573 |
+
"epoch": 1.936,
|
| 1574 |
+
"grad_norm": 0.15557731688022614,
|
| 1575 |
+
"kl": 0.33568115234375,
|
| 1576 |
+
"learning_rate": 1.0105180901839485e-06,
|
| 1577 |
+
"loss": 0.0134,
|
| 1578 |
+
"reward": 1.5648437857627868,
|
| 1579 |
+
"reward_std": 0.4563456516712904,
|
| 1580 |
+
"rewards/accuracy_reward": 0.6401041850447655,
|
| 1581 |
+
"rewards/format_reward": 0.9247396036982536,
|
| 1582 |
+
"step": 1210
|
| 1583 |
+
},
|
| 1584 |
+
{
|
| 1585 |
+
"completion_length": 329.52292518615724,
|
| 1586 |
+
"epoch": 1.952,
|
| 1587 |
+
"grad_norm": 0.35561373829841614,
|
| 1588 |
+
"kl": 0.4545166015625,
|
| 1589 |
+
"learning_rate": 9.84200055904337e-07,
|
| 1590 |
+
"loss": 0.0182,
|
| 1591 |
+
"reward": 1.542187537252903,
|
| 1592 |
+
"reward_std": 0.39646931514143946,
|
| 1593 |
+
"rewards/accuracy_reward": 0.6049479361623525,
|
| 1594 |
+
"rewards/format_reward": 0.9372396036982537,
|
| 1595 |
+
"step": 1220
|
| 1596 |
+
},
|
| 1597 |
+
{
|
| 1598 |
+
"completion_length": 343.41563415527344,
|
| 1599 |
+
"epoch": 1.968,
|
| 1600 |
+
"grad_norm": 0.3309305012226105,
|
| 1601 |
+
"kl": 0.49996337890625,
|
| 1602 |
+
"learning_rate": 9.58060891959604e-07,
|
| 1603 |
+
"loss": 0.02,
|
| 1604 |
+
"reward": 1.484375037252903,
|
| 1605 |
+
"reward_std": 0.44305979572236537,
|
| 1606 |
+
"rewards/accuracy_reward": 0.5619791811332107,
|
| 1607 |
+
"rewards/format_reward": 0.9223958522081375,
|
| 1608 |
+
"step": 1230
|
| 1609 |
+
},
|
| 1610 |
+
{
|
| 1611 |
+
"completion_length": 340.05495872497556,
|
| 1612 |
+
"epoch": 1.984,
|
| 1613 |
+
"grad_norm": 0.17401637136936188,
|
| 1614 |
+
"kl": 0.4303955078125,
|
| 1615 |
+
"learning_rate": 9.321096629513677e-07,
|
| 1616 |
+
"loss": 0.0172,
|
| 1617 |
+
"reward": 1.4763021290302276,
|
| 1618 |
+
"reward_std": 0.4661326684057713,
|
| 1619 |
+
"rewards/accuracy_reward": 0.5549479309469462,
|
| 1620 |
+
"rewards/format_reward": 0.9213541880249977,
|
| 1621 |
+
"step": 1240
|
| 1622 |
+
},
|
| 1623 |
+
{
|
| 1624 |
+
"completion_length": 335.0432403564453,
|
| 1625 |
+
"epoch": 2.0,
|
| 1626 |
+
"grad_norm": 0.10272786021232605,
|
| 1627 |
+
"kl": 0.5320556640625,
|
| 1628 |
+
"learning_rate": 9.063553683087214e-07,
|
| 1629 |
+
"loss": 0.0213,
|
| 1630 |
+
"reward": 1.549739608168602,
|
| 1631 |
+
"reward_std": 0.46059494726359845,
|
| 1632 |
+
"rewards/accuracy_reward": 0.6302083522081375,
|
| 1633 |
+
"rewards/format_reward": 0.9195312708616257,
|
| 1634 |
+
"step": 1250
|
| 1635 |
+
},
|
| 1636 |
+
{
|
| 1637 |
+
"completion_length": 314.4708419799805,
|
| 1638 |
+
"epoch": 2.016,
|
| 1639 |
+
"grad_norm": 0.11312547326087952,
|
| 1640 |
+
"kl": 0.3264892578125,
|
| 1641 |
+
"learning_rate": 8.808069391673894e-07,
|
| 1642 |
+
"loss": 0.0131,
|
| 1643 |
+
"reward": 1.5486979544162751,
|
| 1644 |
+
"reward_std": 0.42191329710185527,
|
| 1645 |
+
"rewards/accuracy_reward": 0.6192708492279053,
|
| 1646 |
+
"rewards/format_reward": 0.929427108168602,
|
| 1647 |
+
"step": 1260
|
| 1648 |
+
},
|
| 1649 |
+
{
|
| 1650 |
+
"completion_length": 324.0794334411621,
|
| 1651 |
+
"epoch": 2.032,
|
| 1652 |
+
"grad_norm": 0.19456617534160614,
|
| 1653 |
+
"kl": 0.3976806640625,
|
| 1654 |
+
"learning_rate": 8.55473235272566e-07,
|
| 1655 |
+
"loss": 0.0159,
|
| 1656 |
+
"reward": 1.5580729603767396,
|
| 1657 |
+
"reward_std": 0.45290672667324544,
|
| 1658 |
+
"rewards/accuracy_reward": 0.6231770989950747,
|
| 1659 |
+
"rewards/format_reward": 0.934895858168602,
|
| 1660 |
+
"step": 1270
|
| 1661 |
+
},
|
| 1662 |
+
{
|
| 1663 |
+
"completion_length": 341.376053237915,
|
| 1664 |
+
"epoch": 2.048,
|
| 1665 |
+
"grad_norm": 0.1282634139060974,
|
| 1666 |
+
"kl": 0.478564453125,
|
| 1667 |
+
"learning_rate": 8.303630419065136e-07,
|
| 1668 |
+
"loss": 0.0191,
|
| 1669 |
+
"reward": 1.5843750417232514,
|
| 1670 |
+
"reward_std": 0.4248688681051135,
|
| 1671 |
+
"rewards/accuracy_reward": 0.6598958525806665,
|
| 1672 |
+
"rewards/format_reward": 0.9244791910052299,
|
| 1673 |
+
"step": 1280
|
| 1674 |
+
},
|
| 1675 |
+
{
|
| 1676 |
+
"completion_length": 351.30183334350585,
|
| 1677 |
+
"epoch": 2.064,
|
| 1678 |
+
"grad_norm": 0.09928528219461441,
|
| 1679 |
+
"kl": 0.44130859375,
|
| 1680 |
+
"learning_rate": 8.054850668419788e-07,
|
| 1681 |
+
"loss": 0.0177,
|
| 1682 |
+
"reward": 1.515104205906391,
|
| 1683 |
+
"reward_std": 0.4964366652071476,
|
| 1684 |
+
"rewards/accuracy_reward": 0.6174479354172945,
|
| 1685 |
+
"rewards/format_reward": 0.8976562708616257,
|
| 1686 |
+
"step": 1290
|
| 1687 |
+
},
|
| 1688 |
+
{
|
| 1689 |
+
"completion_length": 350.6877723693848,
|
| 1690 |
+
"epoch": 2.08,
|
| 1691 |
+
"grad_norm": 0.10390625149011612,
|
| 1692 |
+
"kl": 0.4825927734375,
|
| 1693 |
+
"learning_rate": 7.808479373224925e-07,
|
| 1694 |
+
"loss": 0.0193,
|
| 1695 |
+
"reward": 1.493229202926159,
|
| 1696 |
+
"reward_std": 0.4417869906872511,
|
| 1697 |
+
"rewards/accuracy_reward": 0.5815104300854728,
|
| 1698 |
+
"rewards/format_reward": 0.9117187693715095,
|
| 1699 |
+
"step": 1300
|
| 1700 |
+
},
|
| 1701 |
+
{
|
| 1702 |
+
"completion_length": 334.73959312438967,
|
| 1703 |
+
"epoch": 2.096,
|
| 1704 |
+
"grad_norm": 0.1110270768404007,
|
| 1705 |
+
"kl": 0.76192626953125,
|
| 1706 |
+
"learning_rate": 7.564601970705929e-07,
|
| 1707 |
+
"loss": 0.0306,
|
| 1708 |
+
"reward": 1.510677120089531,
|
| 1709 |
+
"reward_std": 0.4166031703352928,
|
| 1710 |
+
"rewards/accuracy_reward": 0.5739583484828472,
|
| 1711 |
+
"rewards/format_reward": 0.9367187678813934,
|
| 1712 |
+
"step": 1310
|
| 1713 |
+
},
|
| 1714 |
+
{
|
| 1715 |
+
"completion_length": 293.86120681762696,
|
| 1716 |
+
"epoch": 2.112,
|
| 1717 |
+
"grad_norm": 0.1455606073141098,
|
| 1718 |
+
"kl": 0.4578857421875,
|
| 1719 |
+
"learning_rate": 7.323303033250134e-07,
|
| 1720 |
+
"loss": 0.0183,
|
| 1721 |
+
"reward": 1.517187537252903,
|
| 1722 |
+
"reward_std": 0.3795573392882943,
|
| 1723 |
+
"rewards/accuracy_reward": 0.5739583510439843,
|
| 1724 |
+
"rewards/format_reward": 0.9432291880249977,
|
| 1725 |
+
"step": 1320
|
| 1726 |
+
},
|
| 1727 |
+
{
|
| 1728 |
+
"completion_length": 309.1671974182129,
|
| 1729 |
+
"epoch": 2.128,
|
| 1730 |
+
"grad_norm": 0.19481982290744781,
|
| 1731 |
+
"kl": 0.418798828125,
|
| 1732 |
+
"learning_rate": 7.0846662390786e-07,
|
| 1733 |
+
"loss": 0.0167,
|
| 1734 |
+
"reward": 1.4848958790302276,
|
| 1735 |
+
"reward_std": 0.40688302349299194,
|
| 1736 |
+
"rewards/accuracy_reward": 0.5481770981103182,
|
| 1737 |
+
"rewards/format_reward": 0.9367187663912773,
|
| 1738 |
+
"step": 1330
|
| 1739 |
+
},
|
| 1740 |
+
{
|
| 1741 |
+
"completion_length": 330.8593837738037,
|
| 1742 |
+
"epoch": 2.144,
|
| 1743 |
+
"grad_norm": 0.09199036657810211,
|
| 1744 |
+
"kl": 0.44635009765625,
|
| 1745 |
+
"learning_rate": 6.848774343228007e-07,
|
| 1746 |
+
"loss": 0.0179,
|
| 1747 |
+
"reward": 1.4914062917232513,
|
| 1748 |
+
"reward_std": 0.45433705151081083,
|
| 1749 |
+
"rewards/accuracy_reward": 0.5721354318782688,
|
| 1750 |
+
"rewards/format_reward": 0.9192708536982537,
|
| 1751 |
+
"step": 1340
|
| 1752 |
+
},
|
| 1753 |
+
{
|
| 1754 |
+
"completion_length": 338.9346446990967,
|
| 1755 |
+
"epoch": 2.16,
|
| 1756 |
+
"grad_norm": 0.10064072906970978,
|
| 1757 |
+
"kl": 0.5522216796875,
|
| 1758 |
+
"learning_rate": 6.615709148852632e-07,
|
| 1759 |
+
"loss": 0.0221,
|
| 1760 |
+
"reward": 1.5203125387430192,
|
| 1761 |
+
"reward_std": 0.4799085700884461,
|
| 1762 |
+
"rewards/accuracy_reward": 0.6000000141561032,
|
| 1763 |
+
"rewards/format_reward": 0.9203125193715096,
|
| 1764 |
+
"step": 1350
|
| 1765 |
+
},
|
| 1766 |
+
{
|
| 1767 |
+
"completion_length": 322.1612045288086,
|
| 1768 |
+
"epoch": 2.176,
|
| 1769 |
+
"grad_norm": 0.10341834276914597,
|
| 1770 |
+
"kl": 0.4356201171875,
|
| 1771 |
+
"learning_rate": 6.385551478856481e-07,
|
| 1772 |
+
"loss": 0.0174,
|
| 1773 |
+
"reward": 1.5250000357627869,
|
| 1774 |
+
"reward_std": 0.42158898171037434,
|
| 1775 |
+
"rewards/accuracy_reward": 0.5856770953163505,
|
| 1776 |
+
"rewards/format_reward": 0.9393229365348816,
|
| 1777 |
+
"step": 1360
|
| 1778 |
+
},
|
| 1779 |
+
{
|
| 1780 |
+
"completion_length": 319.66303024291994,
|
| 1781 |
+
"epoch": 2.192,
|
| 1782 |
+
"grad_norm": 0.08911896497011185,
|
| 1783 |
+
"kl": 0.33355712890625,
|
| 1784 |
+
"learning_rate": 6.158381147865313e-07,
|
| 1785 |
+
"loss": 0.0134,
|
| 1786 |
+
"reward": 1.6200521171092988,
|
| 1787 |
+
"reward_std": 0.3689839508384466,
|
| 1788 |
+
"rewards/accuracy_reward": 0.6757812671363354,
|
| 1789 |
+
"rewards/format_reward": 0.9442708596587182,
|
| 1790 |
+
"step": 1370
|
| 1791 |
+
},
|
| 1792 |
+
{
|
| 1793 |
+
"completion_length": 306.39219665527344,
|
| 1794 |
+
"epoch": 2.208,
|
| 1795 |
+
"grad_norm": 0.07315315306186676,
|
| 1796 |
+
"kl": 0.65413818359375,
|
| 1797 |
+
"learning_rate": 5.934276934548348e-07,
|
| 1798 |
+
"loss": 0.0262,
|
| 1799 |
+
"reward": 1.5802083760499954,
|
| 1800 |
+
"reward_std": 0.35810978449881076,
|
| 1801 |
+
"rewards/accuracy_reward": 0.6257812708616257,
|
| 1802 |
+
"rewards/format_reward": 0.9544270992279053,
|
| 1803 |
+
"step": 1380
|
| 1804 |
+
},
|
| 1805 |
+
{
|
| 1806 |
+
"completion_length": 351.4132900238037,
|
| 1807 |
+
"epoch": 2.224,
|
| 1808 |
+
"grad_norm": 0.08047836273908615,
|
| 1809 |
+
"kl": 0.442431640625,
|
| 1810 |
+
"learning_rate": 5.713316554299203e-07,
|
| 1811 |
+
"loss": 0.0177,
|
| 1812 |
+
"reward": 1.5190104573965073,
|
| 1813 |
+
"reward_std": 0.4470030918717384,
|
| 1814 |
+
"rewards/accuracy_reward": 0.5908854331821203,
|
| 1815 |
+
"rewards/format_reward": 0.9281250193715096,
|
| 1816 |
+
"step": 1390
|
| 1817 |
+
},
|
| 1818 |
+
{
|
| 1819 |
+
"completion_length": 360.53099937438964,
|
| 1820 |
+
"epoch": 2.24,
|
| 1821 |
+
"grad_norm": 0.1132533922791481,
|
| 1822 |
+
"kl": 0.3490234375,
|
| 1823 |
+
"learning_rate": 5.495576632285572e-07,
|
| 1824 |
+
"loss": 0.014,
|
| 1825 |
+
"reward": 1.596875047683716,
|
| 1826 |
+
"reward_std": 0.42701252046972515,
|
| 1827 |
+
"rewards/accuracy_reward": 0.6643229309469462,
|
| 1828 |
+
"rewards/format_reward": 0.9325521036982536,
|
| 1829 |
+
"step": 1400
|
| 1830 |
+
},
|
| 1831 |
+
{
|
| 1832 |
+
"completion_length": 329.94688377380373,
|
| 1833 |
+
"epoch": 2.2560000000000002,
|
| 1834 |
+
"grad_norm": 0.09439625591039658,
|
| 1835 |
+
"kl": 0.3957763671875,
|
| 1836 |
+
"learning_rate": 5.281132676876946e-07,
|
| 1837 |
+
"loss": 0.0158,
|
| 1838 |
+
"reward": 1.559114620089531,
|
| 1839 |
+
"reward_std": 0.4072124421596527,
|
| 1840 |
+
"rewards/accuracy_reward": 0.6242187682539224,
|
| 1841 |
+
"rewards/format_reward": 0.9348958551883697,
|
| 1842 |
+
"step": 1410
|
| 1843 |
+
},
|
| 1844 |
+
{
|
| 1845 |
+
"completion_length": 331.89454040527346,
|
| 1846 |
+
"epoch": 2.2720000000000002,
|
| 1847 |
+
"grad_norm": 0.2693132162094116,
|
| 1848 |
+
"kl": 0.326708984375,
|
| 1849 |
+
"learning_rate": 5.070059053459672e-07,
|
| 1850 |
+
"loss": 0.0131,
|
| 1851 |
+
"reward": 1.5700521126389504,
|
| 1852 |
+
"reward_std": 0.41562592387199404,
|
| 1853 |
+
"rewards/accuracy_reward": 0.6338541865348816,
|
| 1854 |
+
"rewards/format_reward": 0.9361979395151139,
|
| 1855 |
+
"step": 1420
|
| 1856 |
+
},
|
| 1857 |
+
{
|
| 1858 |
+
"completion_length": 315.82110328674315,
|
| 1859 |
+
"epoch": 2.288,
|
| 1860 |
+
"grad_norm": 0.31827375292778015,
|
| 1861 |
+
"kl": 0.413037109375,
|
| 1862 |
+
"learning_rate": 4.862428958648314e-07,
|
| 1863 |
+
"loss": 0.0165,
|
| 1864 |
+
"reward": 1.5156250312924384,
|
| 1865 |
+
"reward_std": 0.4274031076580286,
|
| 1866 |
+
"rewards/accuracy_reward": 0.5851562664844095,
|
| 1867 |
+
"rewards/format_reward": 0.9304687708616257,
|
| 1868 |
+
"step": 1430
|
| 1869 |
+
},
|
| 1870 |
+
{
|
| 1871 |
+
"completion_length": 309.80261077880857,
|
| 1872 |
+
"epoch": 2.304,
|
| 1873 |
+
"grad_norm": 0.09511108696460724,
|
| 1874 |
+
"kl": 0.5197265625,
|
| 1875 |
+
"learning_rate": 4.6583143949023923e-07,
|
| 1876 |
+
"loss": 0.0208,
|
| 1877 |
+
"reward": 1.5911458671092986,
|
| 1878 |
+
"reward_std": 0.41279490403831004,
|
| 1879 |
+
"rewards/accuracy_reward": 0.6476562671363354,
|
| 1880 |
+
"rewards/format_reward": 0.9434896051883698,
|
| 1881 |
+
"step": 1440
|
| 1882 |
+
},
|
| 1883 |
+
{
|
| 1884 |
+
"completion_length": 317.4851661682129,
|
| 1885 |
+
"epoch": 2.32,
|
| 1886 |
+
"grad_norm": 0.0870954692363739,
|
| 1887 |
+
"kl": 0.705419921875,
|
| 1888 |
+
"learning_rate": 4.4577861455571625e-07,
|
| 1889 |
+
"loss": 0.0282,
|
| 1890 |
+
"reward": 1.541927120089531,
|
| 1891 |
+
"reward_std": 0.44012959226965903,
|
| 1892 |
+
"rewards/accuracy_reward": 0.6156250163912773,
|
| 1893 |
+
"rewards/format_reward": 0.9263021036982536,
|
| 1894 |
+
"step": 1450
|
| 1895 |
+
},
|
| 1896 |
+
{
|
| 1897 |
+
"completion_length": 334.9497497558594,
|
| 1898 |
+
"epoch": 2.336,
|
| 1899 |
+
"grad_norm": 0.10319157689809799,
|
| 1900 |
+
"kl": 0.32333984375,
|
| 1901 |
+
"learning_rate": 4.2609137502772247e-07,
|
| 1902 |
+
"loss": 0.0129,
|
| 1903 |
+
"reward": 1.5619792103767396,
|
| 1904 |
+
"reward_std": 0.4711644366383553,
|
| 1905 |
+
"rewards/accuracy_reward": 0.6453125212341547,
|
| 1906 |
+
"rewards/format_reward": 0.9166666910052299,
|
| 1907 |
+
"step": 1460
|
| 1908 |
+
},
|
| 1909 |
+
{
|
| 1910 |
+
"completion_length": 320.07735481262205,
|
| 1911 |
+
"epoch": 2.352,
|
| 1912 |
+
"grad_norm": 0.1767028421163559,
|
| 1913 |
+
"kl": 0.49638671875,
|
| 1914 |
+
"learning_rate": 4.0677654809413873e-07,
|
| 1915 |
+
"loss": 0.0199,
|
| 1916 |
+
"reward": 1.5223958685994148,
|
| 1917 |
+
"reward_std": 0.40760069973766805,
|
| 1918 |
+
"rewards/accuracy_reward": 0.5927083479939028,
|
| 1919 |
+
"rewards/format_reward": 0.9296875223517418,
|
| 1920 |
+
"step": 1470
|
| 1921 |
+
},
|
| 1922 |
+
{
|
| 1923 |
+
"completion_length": 327.24089736938475,
|
| 1924 |
+
"epoch": 2.368,
|
| 1925 |
+
"grad_norm": 0.13433118164539337,
|
| 1926 |
+
"kl": 0.6244384765625,
|
| 1927 |
+
"learning_rate": 3.878408317967177e-07,
|
| 1928 |
+
"loss": 0.025,
|
| 1929 |
+
"reward": 1.5828125387430192,
|
| 1930 |
+
"reward_std": 0.4388178702443838,
|
| 1931 |
+
"rewards/accuracy_reward": 0.6481770999729634,
|
| 1932 |
+
"rewards/format_reward": 0.9346354365348816,
|
| 1933 |
+
"step": 1480
|
| 1934 |
+
},
|
| 1935 |
+
{
|
| 1936 |
+
"completion_length": 366.6963653564453,
|
| 1937 |
+
"epoch": 2.384,
|
| 1938 |
+
"grad_norm": 0.10366253554821014,
|
| 1939 |
+
"kl": 0.475390625,
|
| 1940 |
+
"learning_rate": 3.6929079270832173e-07,
|
| 1941 |
+
"loss": 0.019,
|
| 1942 |
+
"reward": 1.441927120089531,
|
| 1943 |
+
"reward_std": 0.5121089570224285,
|
| 1944 |
+
"rewards/accuracy_reward": 0.5583333490416408,
|
| 1945 |
+
"rewards/format_reward": 0.8835937723517417,
|
| 1946 |
+
"step": 1490
|
| 1947 |
+
},
|
| 1948 |
+
{
|
| 1949 |
+
"completion_length": 362.4604267120361,
|
| 1950 |
+
"epoch": 2.4,
|
| 1951 |
+
"grad_norm": 0.24114616215229034,
|
| 1952 |
+
"kl": 0.5971923828125,
|
| 1953 |
+
"learning_rate": 3.511328636557509e-07,
|
| 1954 |
+
"loss": 0.0239,
|
| 1955 |
+
"reward": 1.459895870089531,
|
| 1956 |
+
"reward_std": 0.5535307381302118,
|
| 1957 |
+
"rewards/accuracy_reward": 0.5890625186264515,
|
| 1958 |
+
"rewards/format_reward": 0.8708333536982537,
|
| 1959 |
+
"step": 1500
|
| 1960 |
+
},
|
| 1961 |
+
{
|
| 1962 |
+
"completion_length": 378.812771987915,
|
| 1963 |
+
"epoch": 2.416,
|
| 1964 |
+
"grad_norm": 0.5140863060951233,
|
| 1965 |
+
"kl": 0.47861328125,
|
| 1966 |
+
"learning_rate": 3.3337334148895143e-07,
|
| 1967 |
+
"loss": 0.0191,
|
| 1968 |
+
"reward": 1.4708333671092988,
|
| 1969 |
+
"reward_std": 0.5573876537382603,
|
| 1970 |
+
"rewards/accuracy_reward": 0.604427096247673,
|
| 1971 |
+
"rewards/format_reward": 0.8664062723517418,
|
| 1972 |
+
"step": 1510
|
| 1973 |
+
},
|
| 1974 |
+
{
|
| 1975 |
+
"completion_length": 295.7984432220459,
|
| 1976 |
+
"epoch": 2.432,
|
| 1977 |
+
"grad_norm": 0.0825420618057251,
|
| 1978 |
+
"kl": 0.3201416015625,
|
| 1979 |
+
"learning_rate": 3.160183848973795e-07,
|
| 1980 |
+
"loss": 0.0128,
|
| 1981 |
+
"reward": 1.6070312827825546,
|
| 1982 |
+
"reward_std": 0.3443769380450249,
|
| 1983 |
+
"rewards/accuracy_reward": 0.6369791872799396,
|
| 1984 |
+
"rewards/format_reward": 0.9700521051883697,
|
| 1985 |
+
"step": 1520
|
| 1986 |
+
},
|
| 1987 |
+
{
|
| 1988 |
+
"completion_length": 308.06641616821287,
|
| 1989 |
+
"epoch": 2.448,
|
| 1990 |
+
"grad_norm": 0.13088344037532806,
|
| 1991 |
+
"kl": 0.3154541015625,
|
| 1992 |
+
"learning_rate": 2.990740122742765e-07,
|
| 1993 |
+
"loss": 0.0126,
|
| 1994 |
+
"reward": 1.5820313006639481,
|
| 1995 |
+
"reward_std": 0.32235752418637276,
|
| 1996 |
+
"rewards/accuracy_reward": 0.6179687663912773,
|
| 1997 |
+
"rewards/format_reward": 0.9640625208616257,
|
| 1998 |
+
"step": 1530
|
| 1999 |
+
},
|
| 2000 |
+
{
|
| 2001 |
+
"completion_length": 313.82579040527344,
|
| 2002 |
+
"epoch": 2.464,
|
| 2003 |
+
"grad_norm": 0.13155396282672882,
|
| 2004 |
+
"kl": 0.2889404296875,
|
| 2005 |
+
"learning_rate": 2.82546099629595e-07,
|
| 2006 |
+
"loss": 0.0116,
|
| 2007 |
+
"reward": 1.5177083805203437,
|
| 2008 |
+
"reward_std": 0.38207798628136513,
|
| 2009 |
+
"rewards/accuracy_reward": 0.5718750163912774,
|
| 2010 |
+
"rewards/format_reward": 0.9458333477377892,
|
| 2011 |
+
"step": 1540
|
| 2012 |
+
},
|
| 2013 |
+
{
|
| 2014 |
+
"completion_length": 335.9320430755615,
|
| 2015 |
+
"epoch": 2.48,
|
| 2016 |
+
"grad_norm": 0.13609492778778076,
|
| 2017 |
+
"kl": 0.692578125,
|
| 2018 |
+
"learning_rate": 2.664403785523046e-07,
|
| 2019 |
+
"loss": 0.0277,
|
| 2020 |
+
"reward": 1.5653646260499954,
|
| 2021 |
+
"reward_std": 0.457539339363575,
|
| 2022 |
+
"rewards/accuracy_reward": 0.6510416842997074,
|
| 2023 |
+
"rewards/format_reward": 0.9143229365348816,
|
| 2024 |
+
"step": 1550
|
| 2025 |
+
},
|
| 2026 |
+
{
|
| 2027 |
+
"completion_length": 335.92474937438965,
|
| 2028 |
+
"epoch": 2.496,
|
| 2029 |
+
"grad_norm": 0.10897226631641388,
|
| 2030 |
+
"kl": 0.4633544921875,
|
| 2031 |
+
"learning_rate": 2.507624342227748e-07,
|
| 2032 |
+
"loss": 0.0185,
|
| 2033 |
+
"reward": 1.5093750327825546,
|
| 2034 |
+
"reward_std": 0.48894391059875486,
|
| 2035 |
+
"rewards/accuracy_reward": 0.6005208481103181,
|
| 2036 |
+
"rewards/format_reward": 0.9088541865348816,
|
| 2037 |
+
"step": 1560
|
| 2038 |
+
},
|
| 2039 |
+
{
|
| 2040 |
+
"completion_length": 346.82943687438967,
|
| 2041 |
+
"epoch": 2.512,
|
| 2042 |
+
"grad_norm": 0.3290146589279175,
|
| 2043 |
+
"kl": 0.521923828125,
|
| 2044 |
+
"learning_rate": 2.3551770347593443e-07,
|
| 2045 |
+
"loss": 0.0209,
|
| 2046 |
+
"reward": 1.5062500298023225,
|
| 2047 |
+
"reward_std": 0.49438975416123865,
|
| 2048 |
+
"rewards/accuracy_reward": 0.6013021029531955,
|
| 2049 |
+
"rewards/format_reward": 0.9049479335546493,
|
| 2050 |
+
"step": 1570
|
| 2051 |
+
},
|
| 2052 |
+
{
|
| 2053 |
+
"completion_length": 297.566414642334,
|
| 2054 |
+
"epoch": 2.528,
|
| 2055 |
+
"grad_norm": 0.11054307222366333,
|
| 2056 |
+
"kl": 0.3962158203125,
|
| 2057 |
+
"learning_rate": 2.2071147291587318e-07,
|
| 2058 |
+
"loss": 0.0158,
|
| 2059 |
+
"reward": 1.5473958730697632,
|
| 2060 |
+
"reward_std": 0.39565564077347515,
|
| 2061 |
+
"rewards/accuracy_reward": 0.6039062641561032,
|
| 2062 |
+
"rewards/format_reward": 0.9434896051883698,
|
| 2063 |
+
"step": 1580
|
| 2064 |
+
},
|
| 2065 |
+
{
|
| 2066 |
+
"completion_length": 284.1966236114502,
|
| 2067 |
+
"epoch": 2.544,
|
| 2068 |
+
"grad_norm": 0.13115550577640533,
|
| 2069 |
+
"kl": 0.2541015625,
|
| 2070 |
+
"learning_rate": 2.0634887708253957e-07,
|
| 2071 |
+
"loss": 0.0102,
|
| 2072 |
+
"reward": 1.6270833700895309,
|
| 2073 |
+
"reward_std": 0.37217756249010564,
|
| 2074 |
+
"rewards/accuracy_reward": 0.669791679829359,
|
| 2075 |
+
"rewards/format_reward": 0.9572916865348816,
|
| 2076 |
+
"step": 1590
|
| 2077 |
+
},
|
| 2078 |
+
{
|
| 2079 |
+
"completion_length": 299.0880302429199,
|
| 2080 |
+
"epoch": 2.56,
|
| 2081 |
+
"grad_norm": 0.17235107719898224,
|
| 2082 |
+
"kl": 0.345361328125,
|
| 2083 |
+
"learning_rate": 1.9243489667117404e-07,
|
| 2084 |
+
"loss": 0.0138,
|
| 2085 |
+
"reward": 1.496354204416275,
|
| 2086 |
+
"reward_std": 0.4093624118715525,
|
| 2087 |
+
"rewards/accuracy_reward": 0.559635432716459,
|
| 2088 |
+
"rewards/format_reward": 0.9367187663912773,
|
| 2089 |
+
"step": 1600
|
| 2090 |
+
},
|
| 2091 |
+
{
|
| 2092 |
+
"completion_length": 347.20313453674316,
|
| 2093 |
+
"epoch": 2.576,
|
| 2094 |
+
"grad_norm": 0.0926247164607048,
|
| 2095 |
+
"kl": 0.487939453125,
|
| 2096 |
+
"learning_rate": 1.7897435680509044e-07,
|
| 2097 |
+
"loss": 0.0195,
|
| 2098 |
+
"reward": 1.5723958775401115,
|
| 2099 |
+
"reward_std": 0.47892273142933844,
|
| 2100 |
+
"rewards/accuracy_reward": 0.6585937669500709,
|
| 2101 |
+
"rewards/format_reward": 0.9138020992279052,
|
| 2102 |
+
"step": 1610
|
| 2103 |
+
},
|
| 2104 |
+
{
|
| 2105 |
+
"completion_length": 353.61902084350584,
|
| 2106 |
+
"epoch": 2.592,
|
| 2107 |
+
"grad_norm": 0.10807590931653976,
|
| 2108 |
+
"kl": 509.08798828125,
|
| 2109 |
+
"learning_rate": 1.6597192536240918e-07,
|
| 2110 |
+
"loss": 20.4646,
|
| 2111 |
+
"reward": 1.5908854603767395,
|
| 2112 |
+
"reward_std": 0.398144971113652,
|
| 2113 |
+
"rewards/accuracy_reward": 0.649739598762244,
|
| 2114 |
+
"rewards/format_reward": 0.9411458477377892,
|
| 2115 |
+
"step": 1620
|
| 2116 |
+
},
|
| 2117 |
+
{
|
| 2118 |
+
"completion_length": 305.7497501373291,
|
| 2119 |
+
"epoch": 2.608,
|
| 2120 |
+
"grad_norm": 0.05855726823210716,
|
| 2121 |
+
"kl": 0.271142578125,
|
| 2122 |
+
"learning_rate": 1.5343211135731894e-07,
|
| 2123 |
+
"loss": 0.0108,
|
| 2124 |
+
"reward": 1.616406297683716,
|
| 2125 |
+
"reward_std": 0.3559125494211912,
|
| 2126 |
+
"rewards/accuracy_reward": 0.6567708469927311,
|
| 2127 |
+
"rewards/format_reward": 0.9596354380249977,
|
| 2128 |
+
"step": 1630
|
| 2129 |
+
},
|
| 2130 |
+
{
|
| 2131 |
+
"completion_length": 330.2669376373291,
|
| 2132 |
+
"epoch": 2.624,
|
| 2133 |
+
"grad_norm": 0.2727009654045105,
|
| 2134 |
+
"kl": 0.37744140625,
|
| 2135 |
+
"learning_rate": 1.413592633764292e-07,
|
| 2136 |
+
"loss": 0.0151,
|
| 2137 |
+
"reward": 1.6255208760499955,
|
| 2138 |
+
"reward_std": 0.4100566331297159,
|
| 2139 |
+
"rewards/accuracy_reward": 0.6791666850447655,
|
| 2140 |
+
"rewards/format_reward": 0.9463541865348816,
|
| 2141 |
+
"step": 1640
|
| 2142 |
+
},
|
| 2143 |
+
{
|
| 2144 |
+
"completion_length": 314.27292404174807,
|
| 2145 |
+
"epoch": 2.64,
|
| 2146 |
+
"grad_norm": 0.18453815579414368,
|
| 2147 |
+
"kl": 0.3802490234375,
|
| 2148 |
+
"learning_rate": 1.2975756807075945e-07,
|
| 2149 |
+
"loss": 0.0152,
|
| 2150 |
+
"reward": 1.5565104544162751,
|
| 2151 |
+
"reward_std": 0.35327375028282404,
|
| 2152 |
+
"rewards/accuracy_reward": 0.6018229356966913,
|
| 2153 |
+
"rewards/format_reward": 0.9546875223517418,
|
| 2154 |
+
"step": 1650
|
| 2155 |
+
},
|
| 2156 |
+
{
|
| 2157 |
+
"completion_length": 310.15131092071533,
|
| 2158 |
+
"epoch": 2.656,
|
| 2159 |
+
"grad_norm": 0.16150705516338348,
|
| 2160 |
+
"kl": 0.432373046875,
|
| 2161 |
+
"learning_rate": 1.1863104870387903e-07,
|
| 2162 |
+
"loss": 0.0173,
|
| 2163 |
+
"reward": 1.5888021260499954,
|
| 2164 |
+
"reward_std": 0.389334324374795,
|
| 2165 |
+
"rewards/accuracy_reward": 0.6361979298293591,
|
| 2166 |
+
"rewards/format_reward": 0.9526041895151138,
|
| 2167 |
+
"step": 1660
|
| 2168 |
+
},
|
| 2169 |
+
{
|
| 2170 |
+
"completion_length": 343.99792633056643,
|
| 2171 |
+
"epoch": 2.672,
|
| 2172 |
+
"grad_norm": 0.06966466456651688,
|
| 2173 |
+
"kl": 0.6599609375,
|
| 2174 |
+
"learning_rate": 1.0798356375671254e-07,
|
| 2175 |
+
"loss": 0.0264,
|
| 2176 |
+
"reward": 1.5226562947034836,
|
| 2177 |
+
"reward_std": 0.42317282818257806,
|
| 2178 |
+
"rewards/accuracy_reward": 0.5893229354172945,
|
| 2179 |
+
"rewards/format_reward": 0.9333333522081375,
|
| 2180 |
+
"step": 1670
|
| 2181 |
+
},
|
| 2182 |
+
{
|
| 2183 |
+
"completion_length": 347.6976665496826,
|
| 2184 |
+
"epoch": 2.6879999999999997,
|
| 2185 |
+
"grad_norm": 0.08115794509649277,
|
| 2186 |
+
"kl": 0.47548828125,
|
| 2187 |
+
"learning_rate": 9.781880558948619e-08,
|
| 2188 |
+
"loss": 0.019,
|
| 2189 |
+
"reward": 1.5763021200895309,
|
| 2190 |
+
"reward_std": 0.42064056508243086,
|
| 2191 |
+
"rewards/accuracy_reward": 0.6372396051883698,
|
| 2192 |
+
"rewards/format_reward": 0.9390625178813934,
|
| 2193 |
+
"step": 1680
|
| 2194 |
+
},
|
| 2195 |
+
{
|
| 2196 |
+
"completion_length": 333.13386459350585,
|
| 2197 |
+
"epoch": 2.7039999999999997,
|
| 2198 |
+
"grad_norm": 0.31740495562553406,
|
| 2199 |
+
"kl": 0.3748291015625,
|
| 2200 |
+
"learning_rate": 8.81402991612813e-08,
|
| 2201 |
+
"loss": 0.015,
|
| 2202 |
+
"reward": 1.6104167073965072,
|
| 2203 |
+
"reward_std": 0.4134950406849384,
|
| 2204 |
+
"rewards/accuracy_reward": 0.6638021025806665,
|
| 2205 |
+
"rewards/format_reward": 0.9466146036982537,
|
| 2206 |
+
"step": 1690
|
| 2207 |
+
},
|
| 2208 |
+
{
|
| 2209 |
+
"completion_length": 349.80261688232423,
|
| 2210 |
+
"epoch": 2.7199999999999998,
|
| 2211 |
+
"grad_norm": 0.15794631838798523,
|
| 2212 |
+
"kl": 0.6106201171875,
|
| 2213 |
+
"learning_rate": 7.895140080764201e-08,
|
| 2214 |
+
"loss": 0.0244,
|
| 2215 |
+
"reward": 1.4783854544162751,
|
| 2216 |
+
"reward_std": 0.5441196266561746,
|
| 2217 |
+
"rewards/accuracy_reward": 0.5888020968064666,
|
| 2218 |
+
"rewards/format_reward": 0.8895833522081376,
|
| 2219 |
+
"step": 1700
|
| 2220 |
+
},
|
| 2221 |
+
{
|
| 2222 |
+
"completion_length": 341.8935005187988,
|
| 2223 |
+
"epoch": 2.7359999999999998,
|
| 2224 |
+
"grad_norm": 0.13493210077285767,
|
| 2225 |
+
"kl": 0.650341796875,
|
| 2226 |
+
"learning_rate": 7.02552970766569e-08,
|
| 2227 |
+
"loss": 0.026,
|
| 2228 |
+
"reward": 1.546093788743019,
|
| 2229 |
+
"reward_std": 0.5227277502417564,
|
| 2230 |
+
"rewards/accuracy_reward": 0.6377604328095913,
|
| 2231 |
+
"rewards/format_reward": 0.9083333551883698,
|
| 2232 |
+
"step": 1710
|
| 2233 |
+
},
|
| 2234 |
+
{
|
| 2235 |
+
"completion_length": 316.40026931762696,
|
| 2236 |
+
"epoch": 2.752,
|
| 2237 |
+
"grad_norm": 0.17133887112140656,
|
| 2238 |
+
"kl": 0.316015625,
|
| 2239 |
+
"learning_rate": 6.205500362391853e-08,
|
| 2240 |
+
"loss": 0.0126,
|
| 2241 |
+
"reward": 1.5994792133569717,
|
| 2242 |
+
"reward_std": 0.39476869329810144,
|
| 2243 |
+
"rewards/accuracy_reward": 0.6406250201165676,
|
| 2244 |
+
"rewards/format_reward": 0.9588541895151138,
|
| 2245 |
+
"step": 1720
|
| 2246 |
+
},
|
| 2247 |
+
{
|
| 2248 |
+
"completion_length": 309.6942783355713,
|
| 2249 |
+
"epoch": 2.768,
|
| 2250 |
+
"grad_norm": 0.07311931252479553,
|
| 2251 |
+
"kl": 0.47498779296875,
|
| 2252 |
+
"learning_rate": 5.435336416674985e-08,
|
| 2253 |
+
"loss": 0.019,
|
| 2254 |
+
"reward": 1.528906300663948,
|
| 2255 |
+
"reward_std": 0.34818257931619884,
|
| 2256 |
+
"rewards/accuracy_reward": 0.5666666861623526,
|
| 2257 |
+
"rewards/format_reward": 0.9622396036982537,
|
| 2258 |
+
"step": 1730
|
| 2259 |
+
},
|
| 2260 |
+
{
|
| 2261 |
+
"completion_length": 317.2898525238037,
|
| 2262 |
+
"epoch": 2.784,
|
| 2263 |
+
"grad_norm": 0.15522390604019165,
|
| 2264 |
+
"kl": 0.29674072265625,
|
| 2265 |
+
"learning_rate": 4.7153049498051546e-08,
|
| 2266 |
+
"loss": 0.0119,
|
| 2267 |
+
"reward": 1.6304687857627869,
|
| 2268 |
+
"reward_std": 0.35606151502579453,
|
| 2269 |
+
"rewards/accuracy_reward": 0.6640625163912773,
|
| 2270 |
+
"rewards/format_reward": 0.9664062723517418,
|
| 2271 |
+
"step": 1740
|
| 2272 |
+
},
|
| 2273 |
+
{
|
| 2274 |
+
"completion_length": 306.6278762817383,
|
| 2275 |
+
"epoch": 2.8,
|
| 2276 |
+
"grad_norm": 0.09380000084638596,
|
| 2277 |
+
"kl": 0.2547119140625,
|
| 2278 |
+
"learning_rate": 4.0456556560117874e-08,
|
| 2279 |
+
"loss": 0.0102,
|
| 2280 |
+
"reward": 1.6122396111488342,
|
| 2281 |
+
"reward_std": 0.3659005742520094,
|
| 2282 |
+
"rewards/accuracy_reward": 0.6453125214204192,
|
| 2283 |
+
"rewards/format_reward": 0.9669271066784859,
|
| 2284 |
+
"step": 1750
|
| 2285 |
+
},
|
| 2286 |
+
{
|
| 2287 |
+
"completion_length": 322.19063262939454,
|
| 2288 |
+
"epoch": 2.816,
|
| 2289 |
+
"grad_norm": 0.16257521510124207,
|
| 2290 |
+
"kl": 0.37265625,
|
| 2291 |
+
"learning_rate": 3.426620757874266e-08,
|
| 2292 |
+
"loss": 0.0149,
|
| 2293 |
+
"reward": 1.596875038743019,
|
| 2294 |
+
"reward_std": 0.3646328579634428,
|
| 2295 |
+
"rewards/accuracy_reward": 0.6367187672294676,
|
| 2296 |
+
"rewards/format_reward": 0.9601562708616257,
|
| 2297 |
+
"step": 1760
|
| 2298 |
+
},
|
| 2299 |
+
{
|
| 2300 |
+
"completion_length": 369.0770942687988,
|
| 2301 |
+
"epoch": 2.832,
|
| 2302 |
+
"grad_norm": 1.67650306224823,
|
| 2303 |
+
"kl": 0.4777587890625,
|
| 2304 |
+
"learning_rate": 2.858414925791014e-08,
|
| 2305 |
+
"loss": 0.0191,
|
| 2306 |
+
"reward": 1.5520833730697632,
|
| 2307 |
+
"reward_std": 0.5112588044255972,
|
| 2308 |
+
"rewards/accuracy_reward": 0.6450520984828472,
|
| 2309 |
+
"rewards/format_reward": 0.9070312693715096,
|
| 2310 |
+
"step": 1770
|
| 2311 |
+
},
|
| 2312 |
+
{
|
| 2313 |
+
"completion_length": 395.6838626861572,
|
| 2314 |
+
"epoch": 2.848,
|
| 2315 |
+
"grad_norm": 0.08218298107385635,
|
| 2316 |
+
"kl": 0.565185546875,
|
| 2317 |
+
"learning_rate": 2.3412352035357797e-08,
|
| 2318 |
+
"loss": 0.0226,
|
| 2319 |
+
"reward": 1.4523437827825547,
|
| 2320 |
+
"reward_std": 0.5854175344109536,
|
| 2321 |
+
"rewards/accuracy_reward": 0.5934895996004343,
|
| 2322 |
+
"rewards/format_reward": 0.8588541835546494,
|
| 2323 |
+
"step": 1780
|
| 2324 |
+
},
|
| 2325 |
+
{
|
| 2326 |
+
"completion_length": 364.1682384490967,
|
| 2327 |
+
"epoch": 2.864,
|
| 2328 |
+
"grad_norm": 0.1337290108203888,
|
| 2329 |
+
"kl": 0.66181640625,
|
| 2330 |
+
"learning_rate": 1.87526093992616e-08,
|
| 2331 |
+
"loss": 0.0265,
|
| 2332 |
+
"reward": 1.4619792073965072,
|
| 2333 |
+
"reward_std": 0.4972026661038399,
|
| 2334 |
+
"rewards/accuracy_reward": 0.5640625156462192,
|
| 2335 |
+
"rewards/format_reward": 0.8979166850447655,
|
| 2336 |
+
"step": 1790
|
| 2337 |
+
},
|
| 2338 |
+
{
|
| 2339 |
+
"completion_length": 313.5166757583618,
|
| 2340 |
+
"epoch": 2.88,
|
| 2341 |
+
"grad_norm": 0.4620625972747803,
|
| 2342 |
+
"kl": 0.6297607421875,
|
| 2343 |
+
"learning_rate": 1.4606537266287522e-08,
|
| 2344 |
+
"loss": 0.0252,
|
| 2345 |
+
"reward": 1.5656250357627868,
|
| 2346 |
+
"reward_std": 0.42052843160927295,
|
| 2347 |
+
"rewards/accuracy_reward": 0.6260416898876429,
|
| 2348 |
+
"rewards/format_reward": 0.9395833551883698,
|
| 2349 |
+
"step": 1800
|
| 2350 |
+
},
|
| 2351 |
+
{
|
| 2352 |
+
"completion_length": 283.5046951293945,
|
| 2353 |
+
"epoch": 2.896,
|
| 2354 |
+
"grad_norm": 0.14225490391254425,
|
| 2355 |
+
"kl": 0.53448486328125,
|
| 2356 |
+
"learning_rate": 1.0975573421218632e-08,
|
| 2357 |
+
"loss": 0.0214,
|
| 2358 |
+
"reward": 1.6221354603767395,
|
| 2359 |
+
"reward_std": 0.35582950357347726,
|
| 2360 |
+
"rewards/accuracy_reward": 0.6682291835546493,
|
| 2361 |
+
"rewards/format_reward": 0.9539062708616257,
|
| 2362 |
+
"step": 1810
|
| 2363 |
+
},
|
| 2364 |
+
{
|
| 2365 |
+
"completion_length": 329.02943687438966,
|
| 2366 |
+
"epoch": 2.912,
|
| 2367 |
+
"grad_norm": 0.08317083865404129,
|
| 2368 |
+
"kl": 0.330859375,
|
| 2369 |
+
"learning_rate": 7.860977018357751e-09,
|
| 2370 |
+
"loss": 0.0132,
|
| 2371 |
+
"reward": 1.6283854573965073,
|
| 2372 |
+
"reward_std": 0.393698890786618,
|
| 2373 |
+
"rewards/accuracy_reward": 0.6736979335546494,
|
| 2374 |
+
"rewards/format_reward": 0.9546875268220901,
|
| 2375 |
+
"step": 1820
|
| 2376 |
+
},
|
| 2377 |
+
{
|
| 2378 |
+
"completion_length": 336.3953224182129,
|
| 2379 |
+
"epoch": 2.928,
|
| 2380 |
+
"grad_norm": 0.1257566511631012,
|
| 2381 |
+
"kl": 0.5287353515625,
|
| 2382 |
+
"learning_rate": 5.263828144873917e-09,
|
| 2383 |
+
"loss": 0.0212,
|
| 2384 |
+
"reward": 1.5440104603767395,
|
| 2385 |
+
"reward_std": 0.4020043730735779,
|
| 2386 |
+
"rewards/accuracy_reward": 0.5953125171363354,
|
| 2387 |
+
"rewards/format_reward": 0.9486979380249977,
|
| 2388 |
+
"step": 1830
|
| 2389 |
+
},
|
| 2390 |
+
{
|
| 2391 |
+
"completion_length": 359.2218837738037,
|
| 2392 |
+
"epoch": 2.944,
|
| 2393 |
+
"grad_norm": 0.20077994465827942,
|
| 2394 |
+
"kl": 0.4537841796875,
|
| 2395 |
+
"learning_rate": 3.1850274462484896e-09,
|
| 2396 |
+
"loss": 0.0181,
|
| 2397 |
+
"reward": 1.5343750327825547,
|
| 2398 |
+
"reward_std": 0.40093739330768585,
|
| 2399 |
+
"rewards/accuracy_reward": 0.5877604320645332,
|
| 2400 |
+
"rewards/format_reward": 0.9466146022081375,
|
| 2401 |
+
"step": 1840
|
| 2402 |
+
},
|
| 2403 |
+
{
|
| 2404 |
+
"completion_length": 352.94141693115233,
|
| 2405 |
+
"epoch": 2.96,
|
| 2406 |
+
"grad_norm": 0.08914138376712799,
|
| 2407 |
+
"kl": 0.3108154296875,
|
| 2408 |
+
"learning_rate": 1.6252958139456597e-09,
|
| 2409 |
+
"loss": 0.0124,
|
| 2410 |
+
"reward": 1.654687538743019,
|
| 2411 |
+
"reward_std": 0.3981630776077509,
|
| 2412 |
+
"rewards/accuracy_reward": 0.7039062689989806,
|
| 2413 |
+
"rewards/format_reward": 0.9507812678813934,
|
| 2414 |
+
"step": 1850
|
| 2415 |
+
},
|
| 2416 |
+
{
|
| 2417 |
+
"completion_length": 343.89792518615724,
|
| 2418 |
+
"epoch": 2.976,
|
| 2419 |
+
"grad_norm": 0.07618039101362228,
|
| 2420 |
+
"kl": 0.2248779296875,
|
| 2421 |
+
"learning_rate": 5.85174135421418e-10,
|
| 2422 |
+
"loss": 0.009,
|
| 2423 |
+
"reward": 1.6197917073965074,
|
| 2424 |
+
"reward_std": 0.3660704350098968,
|
| 2425 |
+
"rewards/accuracy_reward": 0.6570312656462193,
|
| 2426 |
+
"rewards/format_reward": 0.9627604365348816,
|
| 2427 |
+
"step": 1860
|
| 2428 |
+
},
|
| 2429 |
+
{
|
| 2430 |
+
"completion_length": 344.7703212738037,
|
| 2431 |
+
"epoch": 2.992,
|
| 2432 |
+
"grad_norm": 0.16367003321647644,
|
| 2433 |
+
"kl": 0.4246337890625,
|
| 2434 |
+
"learning_rate": 6.502310655193133e-11,
|
| 2435 |
+
"loss": 0.017,
|
| 2436 |
+
"reward": 1.587239620089531,
|
| 2437 |
+
"reward_std": 0.4006639949977398,
|
| 2438 |
+
"rewards/accuracy_reward": 0.6445312701165676,
|
| 2439 |
+
"rewards/format_reward": 0.9427083522081375,
|
| 2440 |
+
"step": 1870
|
| 2441 |
+
},
|
| 2442 |
+
{
|
| 2443 |
+
"completion_length": 341.2281364440918,
|
| 2444 |
+
"epoch": 3.0,
|
| 2445 |
+
"kl": 0.54423828125,
|
| 2446 |
+
"reward": 1.5484375357627869,
|
| 2447 |
+
"reward_std": 0.4545022763311863,
|
| 2448 |
+
"rewards/accuracy_reward": 0.6192708536982536,
|
| 2449 |
+
"rewards/format_reward": 0.9291666805744171,
|
| 2450 |
+
"step": 1875,
|
| 2451 |
+
"total_flos": 0.0,
|
| 2452 |
+
"train_loss": 0.11509215348958969,
|
| 2453 |
+
"train_runtime": 61764.0604,
|
| 2454 |
+
"train_samples_per_second": 0.364,
|
| 2455 |
+
"train_steps_per_second": 0.03
|
| 2456 |
+
}
|
| 2457 |
+
],
|
| 2458 |
+
"logging_steps": 10,
|
| 2459 |
+
"max_steps": 1875,
|
| 2460 |
+
"num_input_tokens_seen": 0,
|
| 2461 |
+
"num_train_epochs": 3,
|
| 2462 |
+
"save_steps": 500,
|
| 2463 |
+
"stateful_callbacks": {
|
| 2464 |
+
"TrainerControl": {
|
| 2465 |
+
"args": {
|
| 2466 |
+
"should_epoch_stop": false,
|
| 2467 |
+
"should_evaluate": false,
|
| 2468 |
+
"should_log": false,
|
| 2469 |
+
"should_save": true,
|
| 2470 |
+
"should_training_stop": true
|
| 2471 |
+
},
|
| 2472 |
+
"attributes": {}
|
| 2473 |
+
}
|
| 2474 |
+
},
|
| 2475 |
+
"total_flos": 0.0,
|
| 2476 |
+
"train_batch_size": 1,
|
| 2477 |
+
"trial_name": null,
|
| 2478 |
+
"trial_params": null
|
| 2479 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8d79238d3e63d399d212ba5fa35d2af5406413c042d8466d3421ae87535238b0
|
| 3 |
+
size 7096
|
vocab.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
wandb_run_id.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
d1x61l64
|