---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- viggo
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: mixtral-viggo-finetune
  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. -->

# mixtral-viggo-finetune

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the viggo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1785

## 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: 2.5e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6845        | 0.04  | 50   | 0.3694          |
| 0.2931        | 0.08  | 100  | 0.2794          |
| 0.2689        | 0.12  | 150  | 0.2516          |
| 0.2524        | 0.16  | 200  | 0.2398          |
| 0.2226        | 0.2   | 250  | 0.2268          |
| 0.2195        | 0.24  | 300  | 0.2211          |
| 0.2081        | 0.27  | 350  | 0.2141          |
| 0.2052        | 0.31  | 400  | 0.2085          |
| 0.1982        | 0.35  | 450  | 0.2040          |
| 0.2004        | 0.39  | 500  | 0.1974          |
| 0.1889        | 0.43  | 550  | 0.1931          |
| 0.1929        | 0.47  | 600  | 0.1891          |
| 0.185         | 0.51  | 650  | 0.1872          |
| 0.1925        | 0.55  | 700  | 0.1846          |
| 0.1778        | 0.59  | 750  | 0.1885          |
| 0.1741        | 0.63  | 800  | 0.1809          |
| 0.1746        | 0.67  | 850  | 0.1802          |
| 0.1769        | 0.71  | 900  | 0.1792          |
| 0.1795        | 0.74  | 950  | 0.1785          |
| 0.158         | 0.78  | 1000 | 0.1785          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0