---
base_model: mistralai/Mistral-7B-Instruct-v0.3
datasets:
- GaetanMichelet/chat-60_ft_task-2_auto
- GaetanMichelet/chat-120_ft_task-2_auto
- GaetanMichelet/chat-180_ft_task-2_auto
library_name: peft
license: apache-2.0
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Mistral-7B_task-2_180-samples_config-1_auto
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B_task-2_180-samples_config-1_auto

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the GaetanMichelet/chat-60_ft_task-2_auto, the GaetanMichelet/chat-120_ft_task-2_auto and the GaetanMichelet/chat-180_ft_task-2_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4650

## 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: 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6307        | 1.0   | 17   | 0.6122          |
| 0.5229        | 2.0   | 34   | 0.5022          |
| 0.4431        | 3.0   | 51   | 0.4650          |
| 0.3222        | 4.0   | 68   | 0.4746          |
| 0.2227        | 5.0   | 85   | 0.5481          |
| 0.1345        | 6.0   | 102  | 0.6141          |
| 0.0738        | 7.0   | 119  | 0.6842          |
| 0.0448        | 8.0   | 136  | 0.7531          |
| 0.0352        | 9.0   | 153  | 0.8120          |
| 0.0246        | 10.0  | 170  | 0.8534          |


### Framework versions

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