---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-2_auto
- GaetanMichelet/chat-120_ft_task-2_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-2_120-samples_config-2_auto
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-31-8B_task-2_120-samples_config-2_auto

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-2_auto and the GaetanMichelet/chat-120_ft_task-2_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.5819

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.9245        | 0.9091  | 5    | 0.8871          |
| 0.8834        | 2.0     | 11   | 0.7984          |
| 0.7224        | 2.9091  | 16   | 0.7230          |
| 0.6496        | 4.0     | 22   | 0.6428          |
| 0.5918        | 4.9091  | 27   | 0.6049          |
| 0.5484        | 6.0     | 33   | 0.5821          |
| 0.472         | 6.9091  | 38   | 0.5819          |
| 0.4328        | 8.0     | 44   | 0.5885          |
| 0.3688        | 8.9091  | 49   | 0.6169          |
| 0.2923        | 10.0    | 55   | 0.6638          |
| 0.2063        | 10.9091 | 60   | 0.7679          |
| 0.1206        | 12.0    | 66   | 0.8585          |
| 0.0643        | 12.9091 | 71   | 1.0241          |
| 0.0373        | 14.0    | 77   | 1.0912          |


### Framework versions

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