---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.1
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: original_glue_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. -->

# original_glue_cola

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3803
- Accuracy: 0.8363

## 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: 8
- eval_batch_size: 16
- seed: 0
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4253        | 0.22  | 50   | 0.4968          | 0.7553   |
| 0.5036        | 0.44  | 100  | 0.4704          | 0.7779   |
| 0.4974        | 0.66  | 150  | 0.4562          | 0.7825   |
| 0.4649        | 0.88  | 200  | 0.4299          | 0.7880   |
| 0.3356        | 1.1   | 250  | 0.4155          | 0.8051   |
| 0.4005        | 1.32  | 300  | 0.4026          | 0.8184   |
| 0.328         | 1.54  | 350  | 0.4052          | 0.8145   |
| 0.3632        | 1.76  | 400  | 0.3889          | 0.8270   |
| 0.3334        | 1.98  | 450  | 0.4176          | 0.8036   |
| 0.3166        | 2.2   | 500  | 0.4195          | 0.8324   |
| 0.2649        | 2.42  | 550  | 0.3929          | 0.8254   |
| 0.2805        | 2.64  | 600  | 0.3877          | 0.8363   |
| 0.3357        | 2.86  | 650  | 0.3734          | 0.8457   |
| 0.2476        | 3.08  | 700  | 0.3930          | 0.8418   |
| 0.2361        | 3.3   | 750  | 0.3893          | 0.8566   |
| 0.2375        | 3.52  | 800  | 0.3769          | 0.8519   |
| 0.18          | 3.74  | 850  | 0.3757          | 0.8519   |
| 0.2305        | 3.96  | 900  | 0.3783          | 0.8465   |
| 0.1432        | 4.18  | 950  | 0.4876          | 0.8402   |


### Framework versions

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