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
- matthews_correlation
model-index:
- name: Mistral-7B-v0.1_cola_original2
  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_original2

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: 0.3773
- Accuracy: {'accuracy': 0.8539719626168224}
- Matthews Correlation: 0.6454

## 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
- total_train_batch_size: 384
- 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                         | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|:--------------------:|
| 0.4986        | 2.38  | 50   | 0.5042          | {'accuracy': 0.7938638542665388} | 0.4836               |
| 0.3193        | 4.76  | 100  | 0.4002          | {'accuracy': 0.8264621284755513} | 0.6029               |
| 0.2489        | 7.14  | 150  | 0.3795          | {'accuracy': 0.8389261744966443} | 0.6123               |
| 0.1258        | 9.52  | 200  | 0.4322          | {'accuracy': 0.8418024928092043} | 0.6284               |
| 0.0625        | 11.9  | 250  | 0.5921          | {'accuracy': 0.8427612655800575} | 0.6258               |
| 0.0251        | 14.29 | 300  | 0.8451          | {'accuracy': 0.8446788111217641} | 0.6248               |


### Framework versions

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