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

# mistral-viggo-finetune

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: 0.4072

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4563        | 0.01  | 50   | 0.7277          |
| 0.5873        | 0.01  | 100  | 0.5276          |
| 0.4951        | 0.02  | 150  | 0.4817          |
| 0.4645        | 0.02  | 200  | 0.4664          |
| 0.4682        | 0.03  | 250  | 0.4541          |
| 0.4569        | 0.03  | 300  | 0.4447          |
| 0.4428        | 0.04  | 350  | 0.4362          |
| 0.4184        | 0.04  | 400  | 0.4326          |
| 0.4174        | 0.05  | 450  | 0.4280          |
| 0.4122        | 0.05  | 500  | 0.4242          |
| 0.4176        | 0.06  | 550  | 0.4228          |
| 0.4105        | 0.06  | 600  | 0.4175          |
| 0.4103        | 0.07  | 650  | 0.4154          |
| 0.4113        | 0.07  | 700  | 0.4133          |
| 0.3979        | 0.08  | 750  | 0.4118          |
| 0.3895        | 0.08  | 800  | 0.4109          |
| 0.4088        | 0.09  | 850  | 0.4092          |
| 0.399         | 0.09  | 900  | 0.4082          |
| 0.4001        | 0.1   | 950  | 0.4075          |
| 0.4067        | 0.1   | 1000 | 0.4072          |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1