safetensors generated_from_trainer base_model:mistralai/Mistral-7B-v0.1 license:apache-2.0 region:us
---
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_ignore_none
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Mistral-7B-v0.1_cola_ignore_none

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: 0.5376
- Accuracy: 0.8318

## 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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2085        | 1.61  | 25   | 1.2708          | 0.5695   |
| 0.7114        | 3.23  | 50   | 0.7877          | 0.6913   |
| 0.6189        | 4.84  | 75   | 0.6380          | 0.7258   |
| 0.6101        | 6.45  | 100  | 0.6412          | 0.7411   |
| 0.4509        | 8.06  | 125  | 0.5499          | 0.7622   |
| 0.4873        | 9.68  | 150  | 0.5194          | 0.7756   |
| 0.4272        | 11.29 | 175  | 0.5000          | 0.7929   |
| 0.3804        | 12.9  | 200  | 0.4769          | 0.8073   |
| 0.3547        | 14.52 | 225  | 0.4611          | 0.8121   |
| 0.3394        | 16.13 | 250  | 0.4567          | 0.8130   |
| 0.3945        | 17.74 | 275  | 0.4237          | 0.8351   |
| 0.313         | 19.35 | 300  | 0.4182          | 0.8332   |
| 0.2822        | 20.97 | 325  | 0.4205          | 0.8389   |
| 0.293         | 22.58 | 350  | 0.4153          | 0.8370   |
| 0.2449        | 24.19 | 375  | 0.4229          | 0.8341   |
| 0.1968        | 25.81 | 400  | 0.4439          | 0.8341   |
| 0.1868        | 27.42 | 425  | 0.4428          | 0.8360   |
| 0.1395        | 29.03 | 450  | 0.4913          | 0.8284   |
| 0.1583        | 30.65 | 475  | 0.4841          | 0.8245   |
| 0.2198        | 32.26 | 500  | 0.5471          | 0.8207   |
| 0.0953        | 33.87 | 525  | 0.5189          | 0.8351   |
| 0.1583        | 35.48 | 550  | 0.5668          | 0.8265   |
| 0.0988        | 37.1  | 575  | 0.5778          | 0.8217   |
| 0.0451        | 38.71 | 600  | 0.6536          | 0.8313   |


### Framework versions

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