---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_120-samples_config-3_full
  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. -->

# Llama-31-8B_task-1_120-samples_config-3_full

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9369

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 150

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4681        | 1.0   | 11   | 2.4539          |
| 2.3894        | 2.0   | 22   | 2.4260          |
| 2.4746        | 3.0   | 33   | 2.3827          |
| 2.4177        | 4.0   | 44   | 2.3138          |
| 2.1959        | 5.0   | 55   | 2.2269          |
| 2.16          | 6.0   | 66   | 2.1177          |
| 2.0388        | 7.0   | 77   | 1.9844          |
| 1.8932        | 8.0   | 88   | 1.8442          |
| 1.7199        | 9.0   | 99   | 1.6830          |
| 1.4973        | 10.0  | 110  | 1.4929          |
| 1.2726        | 11.0  | 121  | 1.2980          |
| 1.204         | 12.0  | 132  | 1.1554          |
| 1.0597        | 13.0  | 143  | 1.0772          |
| 1.0642        | 14.0  | 154  | 1.0425          |
| 1.0466        | 15.0  | 165  | 1.0201          |
| 1.0044        | 16.0  | 176  | 1.0010          |
| 0.9967        | 17.0  | 187  | 0.9866          |
| 0.9863        | 18.0  | 198  | 0.9736          |
| 0.9065        | 19.0  | 209  | 0.9644          |
| 0.8669        | 20.0  | 220  | 0.9539          |
| 0.9253        | 21.0  | 231  | 0.9454          |
| 0.872         | 22.0  | 242  | 0.9398          |
| 0.8824        | 23.0  | 253  | 0.9328          |
| 0.8582        | 24.0  | 264  | 0.9283          |
| 0.8763        | 25.0  | 275  | 0.9221          |
| 0.8199        | 26.0  | 286  | 0.9177          |
| 0.7986        | 27.0  | 297  | 0.9146          |
| 0.7754        | 28.0  | 308  | 0.9142          |
| 0.7893        | 29.0  | 319  | 0.9086          |
| 0.7312        | 30.0  | 330  | 0.9087          |
| 0.7431        | 31.0  | 341  | 0.9050          |
| 0.7103        | 32.0  | 352  | 0.9037          |
| 0.6967        | 33.0  | 363  | 0.9092          |
| 0.6502        | 34.0  | 374  | 0.9071          |
| 0.6659        | 35.0  | 385  | 0.9019          |
| 0.7003        | 36.0  | 396  | 0.9015          |
| 0.629         | 37.0  | 407  | 0.9018          |
| 0.6299        | 38.0  | 418  | 0.9081          |
| 0.6259        | 39.0  | 429  | 0.9162          |
| 0.6262        | 40.0  | 440  | 0.9212          |
| 0.5707        | 41.0  | 451  | 0.9212          |
| 0.5749        | 42.0  | 462  | 0.9274          |
| 0.533         | 43.0  | 473  | 0.9369          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1