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# v12_bert-base-uncased-finetuned-mrpc

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7151
- Accuracy: 0.7623
- F1: 0.8418

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 63
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4064        | 1.0   | 719  | 0.6134          | 0.8015   | 0.8643 |
| 0.1426        | 2.0   | 1438 | 1.2114          | 0.7696   | 0.8479 |
| 0.0209        | 3.0   | 2157 | 1.4115          | 0.7819   | 0.8514 |
| 0.0136        | 4.0   | 2876 | 1.5548          | 0.7672   | 0.8403 |
| 0.0041        | 5.0   | 3595 | 1.7151          | 0.7623   | 0.8418 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "v12_bert-base-uncased-finetuned-mrpc", "results": []}]}
transformers pytorch tensorboard bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us