---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-3
- GaetanMichelet/chat-120_ft_task-3
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-3_120-samples_config-3
  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-3_120-samples_config-3

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 GaetanMichelet/chat-60_ft_task-3 and the GaetanMichelet/chat-120_ft_task-3 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4408

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.3729        | 1.0   | 11   | 2.4972          |
| 2.6938        | 2.0   | 22   | 2.4571          |
| 2.6474        | 3.0   | 33   | 2.3881          |
| 2.2763        | 4.0   | 44   | 2.2642          |
| 2.0268        | 5.0   | 55   | 2.0694          |
| 1.7309        | 6.0   | 66   | 1.7871          |
| 1.4481        | 7.0   | 77   | 1.4330          |
| 1.0554        | 8.0   | 88   | 1.0675          |
| 0.8392        | 9.0   | 99   | 0.7563          |
| 0.4685        | 10.0  | 110  | 0.6437          |
| 0.3588        | 11.0  | 121  | 0.5851          |
| 0.6319        | 12.0  | 132  | 0.5407          |
| 0.4211        | 13.0  | 143  | 0.5248          |
| 0.495         | 14.0  | 154  | 0.5127          |
| 0.4232        | 15.0  | 165  | 0.5019          |
| 0.496         | 16.0  | 176  | 0.5103          |
| 0.3903        | 17.0  | 187  | 0.4814          |
| 0.331         | 18.0  | 198  | 0.4913          |
| 0.2403        | 19.0  | 209  | 0.4869          |
| 0.3563        | 20.0  | 220  | 0.4718          |
| 0.4107        | 21.0  | 231  | 0.4596          |
| 0.2631        | 22.0  | 242  | 0.4478          |
| 0.4212        | 23.0  | 253  | 0.4496          |
| 0.3304        | 24.0  | 264  | 0.4408          |
| 0.3296        | 25.0  | 275  | 0.4437          |
| 0.3266        | 26.0  | 286  | 0.4441          |
| 0.1403        | 27.0  | 297  | 0.4496          |
| 0.1732        | 28.0  | 308  | 0.4574          |
| 0.1797        | 29.0  | 319  | 0.4809          |
| 0.1355        | 30.0  | 330  | 0.4990          |
| 0.1346        | 31.0  | 341  | 0.5313          |


### Framework versions

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