---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
model-index:
- name: mistral_o1_5_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. -->

# mistral_o1_5_full

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5849

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_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: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7053        | 0.0824 | 100  | 0.7166          |
| 0.7157        | 0.1648 | 200  | 0.7360          |
| 0.7015        | 0.2472 | 300  | 0.7378          |
| 0.6937        | 0.3296 | 400  | 0.7115          |
| 0.6718        | 0.4120 | 500  | 0.6946          |
| 0.6401        | 0.4944 | 600  | 0.6726          |
| 0.6232        | 0.5768 | 700  | 0.6494          |
| 0.6021        | 0.6593 | 800  | 0.6263          |
| 0.5771        | 0.7417 | 900  | 0.6054          |
| 0.5587        | 0.8241 | 1000 | 0.5935          |
| 0.5512        | 0.9065 | 1100 | 0.5863          |
| 0.5406        | 0.9889 | 1200 | 0.5847          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1