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

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: 0.9858
- Accuracy: 0.8692

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 2
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 2
- total_train_batch_size: 768
- total_eval_batch_size: 384
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 750

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0563        | 2.38  | 25   | 1.1091          | 0.6347   |
| 0.7148        | 4.76  | 50   | 0.7231          | 0.7210   |
| 0.5436        | 7.14  | 75   | 0.5349          | 0.7929   |
| 0.4144        | 9.52  | 100  | 0.4578          | 0.8159   |
| 0.3537        | 11.9  | 125  | 0.4236          | 0.8207   |
| 0.3208        | 14.29 | 150  | 0.3996          | 0.8274   |
| 0.3204        | 16.67 | 175  | 0.3874          | 0.8322   |
| 0.2888        | 19.05 | 200  | 0.3939          | 0.8351   |
| 0.2629        | 21.43 | 225  | 0.3837          | 0.8341   |
| 0.2288        | 23.81 | 250  | 0.3904          | 0.8437   |
| 0.1757        | 26.19 | 275  | 0.4016          | 0.8456   |
| 0.1754        | 28.57 | 300  | 0.4165          | 0.8428   |
| 0.1137        | 30.95 | 325  | 0.4513          | 0.8447   |
| 0.0611        | 33.33 | 350  | 0.5193          | 0.8399   |
| 0.0555        | 35.71 | 375  | 0.5863          | 0.8428   |
| 0.0346        | 38.1  | 400  | 0.7369          | 0.8313   |
| 0.0125        | 40.48 | 425  | 0.7936          | 0.8360   |
| 0.0041        | 42.86 | 450  | 0.8821          | 0.8351   |
| 0.0052        | 45.24 | 475  | 0.9493          | 0.8332   |
| 0.0121        | 47.62 | 500  | 1.0594          | 0.8380   |
| 0.0063        | 50.0  | 525  | 1.0706          | 0.8332   |
| 0.0025        | 52.38 | 550  | 1.0518          | 0.8303   |
| 0.0115        | 54.76 | 575  | 1.0344          | 0.8360   |
| 0.0167        | 57.14 | 600  | 1.1477          | 0.8322   |
| 0.0096        | 59.52 | 625  | 1.1863          | 0.8341   |
| 0.004         | 61.9  | 650  | 1.1809          | 0.8399   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0