---
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
datasets:
- generator
model-index:
- name: mistral_o1_10_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_10_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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6912

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.79          | 0.0622 | 100  | 0.8509          |
| 0.7592        | 0.1245 | 200  | 0.9030          |
| 0.7628        | 0.1867 | 300  | 0.8635          |
| 0.7546        | 0.2489 | 400  | 0.8601          |
| 0.7427        | 0.3111 | 500  | 0.8204          |
| 0.7268        | 0.3734 | 600  | 0.8335          |
| 0.7084        | 0.4356 | 700  | 0.8025          |
| 0.6958        | 0.4978 | 800  | 0.7765          |
| 0.6789        | 0.5600 | 900  | 0.7588          |
| 0.6506        | 0.6223 | 1000 | 0.7463          |
| 0.645         | 0.6845 | 1100 | 0.7306          |
| 0.6335        | 0.7467 | 1200 | 0.7130          |
| 0.615         | 0.8090 | 1300 | 0.7026          |
| 0.608         | 0.8712 | 1400 | 0.6949          |
| 0.604         | 0.9334 | 1500 | 0.6919          |
| 0.6039        | 0.9956 | 1600 | 0.6911          |


### Framework versions

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