---
library_name: peft
license: apache-2.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v0.6
tags:
- axolotl
- generated_from_trainer
model-index:
- name: ad641a5b-ef11-4278-80e4-9119f53c47f4
  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: TinyLlama/TinyLlama-1.1B-Chat-v0.6
batch_size: 8
bf16: true
chat_template: tokenizer_default_fallback_alpaca
datasets:
- data_files:
  - 11bfaf21b106be7f_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/11bfaf21b106be7f_train_data.json
  type:
    field_input: project_and_commit_id
    field_instruction: source
    field_output: target
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
early_stopping_patience: 3
eval_steps: 50
flash_attention: true
gpu_memory_limit: 80GiB
gradient_checkpointing: true
group_by_length: true
hub_model_id: willtensora/ad641a5b-ef11-4278-80e4-9119f53c47f4
hub_strategy: checkpoint
learning_rate: 0.0002
logging_steps: 10
lora_alpha: 256
lora_dropout: 0.1
lora_r: 128
lora_target_linear: true
lr_scheduler: cosine
micro_batch_size: 1
model_type: AutoModelForCausalLM
num_epochs: 100
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resize_token_embeddings_to_32x: false
sample_packing: false
save_steps: 50
sequence_len: 2048
tokenizer_type: LlamaTokenizerFast
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.1
wandb_entity: ''
wandb_mode: online
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: default
warmup_ratio: 0.05
xformers_attention: true

```

</details><br>

# ad641a5b-ef11-4278-80e4-9119f53c47f4

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v0.6](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2704

## 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
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- 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: 589
- num_epochs: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0011 | 1    | 2.0060          |
| 1.2664        | 0.0530 | 50   | 1.2713          |
| 0.9659        | 0.1060 | 100  | 0.9642          |
| 0.7596        | 0.1591 | 150  | 0.8311          |
| 0.7092        | 0.2121 | 200  | 0.7583          |
| 0.6691        | 0.2651 | 250  | 0.6944          |
| 0.65          | 0.3181 | 300  | 0.6577          |
| 0.6149        | 0.3712 | 350  | 0.6268          |
| 0.5929        | 0.4242 | 400  | 0.5945          |
| 0.5319        | 0.4772 | 450  | 0.5820          |
| 0.5136        | 0.5302 | 500  | 0.5576          |
| 0.5258        | 0.5832 | 550  | 0.5367          |
| 0.4476        | 0.6363 | 600  | 0.5141          |
| 0.5018        | 0.6893 | 650  | 0.4943          |
| 0.4851        | 0.7423 | 700  | 0.4861          |
| 0.41          | 0.7953 | 750  | 0.4693          |
| 0.4625        | 0.8484 | 800  | 0.4552          |
| 0.4909        | 0.9014 | 850  | 0.4421          |
| 0.3885        | 0.9544 | 900  | 0.4196          |
| 0.3408        | 1.0074 | 950  | 0.4111          |
| 0.2804        | 1.0604 | 1000 | 0.4020          |
| 0.3503        | 1.1135 | 1050 | 0.3875          |
| 0.291         | 1.1665 | 1100 | 0.3958          |
| 0.3025        | 1.2195 | 1150 | 0.3849          |
| 0.2749        | 1.2725 | 1200 | 0.3729          |
| 0.3222        | 1.3256 | 1250 | 0.3631          |
| 0.2895        | 1.3786 | 1300 | 0.3570          |
| 0.2994        | 1.4316 | 1350 | 0.3470          |
| 0.3055        | 1.4846 | 1400 | 0.3431          |
| 0.2252        | 1.5376 | 1450 | 0.3351          |
| 0.2816        | 1.5907 | 1500 | 0.3214          |
| 0.3065        | 1.6437 | 1550 | 0.3163          |
| 0.2727        | 1.6967 | 1600 | 0.3158          |
| 0.2673        | 1.7497 | 1650 | 0.3123          |
| 0.276         | 1.8028 | 1700 | 0.3090          |
| 0.217         | 1.8558 | 1750 | 0.3021          |
| 0.2712        | 1.9088 | 1800 | 0.2950          |
| 0.2175        | 1.9618 | 1850 | 0.2927          |
| 0.1561        | 2.0148 | 1900 | 0.2911          |
| 0.1557        | 2.0679 | 1950 | 0.2773          |
| 0.1404        | 2.1209 | 2000 | 0.2725          |
| 0.1386        | 2.1739 | 2050 | 0.2696          |
| 0.1224        | 2.2269 | 2100 | 0.2780          |
| 0.1535        | 2.2800 | 2150 | 0.2713          |
| 0.1494        | 2.3330 | 2200 | 0.2704          |


### Framework versions

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