---
library_name: peft
license: apache-2.0
base_model: openlm-research/open_llama_3b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: b04780ef-9f9b-425c-8e3a-41c0a82a1156
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
adapter: qlora
auto_resume_from_checkpoints: true
base_model: openlm-research/open_llama_3b
bf16: true
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 1
datasets:
- data_files:
  - 5668b44a803035dd_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/5668b44a803035dd_train_data.json
  type:
    field_input: concepts
    field_instruction: instruction
    field_output: response
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 200
eval_table_size: null
evals_per_epoch:
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: error577/b04780ef-9f9b-425c-8e3a-41c0a82a1156
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps:
micro_batch_size: 1
mlflow_experiment_name: /tmp/5668b44a803035dd_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 200
sequence_len: 512
special_tokens:
  pad_token: </s>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: eeda891a-7fde-4fb3-9e00-351e4d608c46
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: eeda891a-7fde-4fb3-9e00-351e4d608c46
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# b04780ef-9f9b-425c-8e3a-41c0a82a1156

This model is a fine-tuned version of [openlm-research/open_llama_3b](https://huggingface.co/openlm-research/open_llama_3b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4543

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8702        | 0.0001 | 1    | 0.9949          |
| 0.6079        | 0.0160 | 200  | 0.4871          |
| 0.4528        | 0.0319 | 400  | 0.4786          |
| 0.2824        | 0.0479 | 600  | 0.4708          |
| 0.3962        | 0.0639 | 800  | 0.4652          |
| 0.476         | 0.0798 | 1000 | 0.4598          |
| 0.5171        | 0.0958 | 1200 | 0.4604          |
| 0.4526        | 0.1118 | 1400 | 0.4589          |
| 0.3575        | 0.1277 | 1600 | 0.4584          |
| 0.4238        | 0.1437 | 1800 | 0.4533          |
| 0.3328        | 0.1597 | 2000 | 0.4513          |
| 0.3756        | 0.1756 | 2200 | 0.4549          |
| 0.4138        | 0.1916 | 2400 | 0.4504          |
| 0.3911        | 0.2075 | 2600 | 0.4506          |
| 0.4822        | 0.2235 | 2800 | 0.4514          |
| 0.4627        | 0.2395 | 3000 | 0.4543          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1