---
library_name: peft
license: apache-2.0
base_model: unsloth/tinyllama-chat
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 8d2d892c-ff6e-4848-9b91-107eb3356cd9
  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: lora
base_model: unsloth/tinyllama-chat
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - daed85532ae01daa_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/daed85532ae01daa_train_data.json
  type:
    field_input: input
    field_instruction: instruction
    field_output: output
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map:
  ? ''
  : 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/8d2d892c-ff6e-4848-9b91-107eb3356cd9
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 3436
micro_batch_size: 4
mlflow_experiment_name: /tmp/daed85532ae01daa_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
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: 100
sequence_len: 2048
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: d7c344bd-e406-41ee-ad84-5b799adb7e49
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: d7c344bd-e406-41ee-ad84-5b799adb7e49
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 8d2d892c-ff6e-4848-9b91-107eb3356cd9

This model is a fine-tuned version of [unsloth/tinyllama-chat](https://huggingface.co/unsloth/tinyllama-chat) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0690

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 10
- training_steps: 3436

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7226        | 0.0004 | 1    | 1.8629          |
| 1.5389        | 0.0413 | 100  | 1.5883          |
| 1.6151        | 0.0826 | 200  | 1.5001          |
| 1.4608        | 0.1239 | 300  | 1.4470          |
| 1.391         | 0.1652 | 400  | 1.4021          |
| 1.4795        | 0.2065 | 500  | 1.3675          |
| 1.3089        | 0.2478 | 600  | 1.3393          |
| 1.2863        | 0.2891 | 700  | 1.3107          |
| 1.2662        | 0.3304 | 800  | 1.2906          |
| 1.0741        | 0.3717 | 900  | 1.2695          |
| 1.3393        | 0.4130 | 1000 | 1.2517          |
| 1.2022        | 0.4543 | 1100 | 1.2325          |
| 1.2035        | 0.4956 | 1200 | 1.2130          |
| 1.1916        | 0.5369 | 1300 | 1.2001          |
| 1.194         | 0.5782 | 1400 | 1.1885          |
| 1.1436        | 0.6195 | 1500 | 1.1722          |
| 1.1657        | 0.6608 | 1600 | 1.1645          |
| 1.2633        | 0.7022 | 1700 | 1.1506          |
| 1.1023        | 0.7435 | 1800 | 1.1378          |
| 1.083         | 0.7848 | 1900 | 1.1263          |
| 1.1029        | 0.8261 | 2000 | 1.1195          |
| 1.2289        | 0.8674 | 2100 | 1.1089          |
| 1.0197        | 0.9087 | 2200 | 1.1006          |
| 1.0328        | 0.9500 | 2300 | 1.0929          |
| 1.0541        | 0.9913 | 2400 | 1.0857          |
| 0.9552        | 1.0326 | 2500 | 1.0857          |
| 0.8904        | 1.0739 | 2600 | 1.0828          |
| 0.9669        | 1.1152 | 2700 | 1.0780          |
| 1.0052        | 1.1565 | 2800 | 1.0762          |
| 0.9452        | 1.1978 | 2900 | 1.0731          |
| 0.876         | 1.2391 | 3000 | 1.0715          |
| 0.937         | 1.2804 | 3100 | 1.0701          |
| 1.0547        | 1.3217 | 3200 | 1.0692          |
| 0.8701        | 1.3630 | 3300 | 1.0691          |
| 1.1223        | 1.4043 | 3400 | 1.0690          |


### Framework versions

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