---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- generated_from_trainer
model-index:
- name: Mistral-7b
  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-7b

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1919

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 32
- total_train_batch_size: 2048
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 12.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7591        | 0.64  | 25   | 4.9279          |
| 2.0299        | 1.28  | 50   | 0.8182          |
| 0.6558        | 1.92  | 75   | 0.5750          |
| 0.4785        | 2.56  | 100  | 0.3823          |
| 0.3837        | 3.2   | 125  | 0.2941          |
| 0.3073        | 3.84  | 150  | 0.2318          |
| 0.2119        | 4.48  | 175  | 0.1871          |
| 0.1632        | 5.12  | 200  | 0.1595          |
| 0.1297        | 5.76  | 225  | 0.1487          |
| 0.1035        | 6.39  | 250  | 0.1476          |
| 0.0856        | 7.03  | 275  | 0.1427          |
| 0.0574        | 7.67  | 300  | 0.1482          |
| 0.0448        | 8.31  | 325  | 0.1552          |
| 0.0318        | 8.95  | 350  | 0.1562          |
| 0.0196        | 9.59  | 375  | 0.1709          |
| 0.0146        | 10.23 | 400  | 0.1793          |
| 0.0084        | 10.87 | 425  | 0.1854          |
| 0.0058        | 11.51 | 450  | 0.1919          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2