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# finetuned-bert-mrpc

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4474
- Accuracy: 0.8505
- F1: 0.8957

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5457        | 1.0   | 230  | 0.4346          | 0.8015   | 0.8661 |
| 0.3094        | 2.0   | 460  | 0.4051          | 0.8529   | 0.8980 |
| 0.1424        | 3.0   | 690  | 0.4474          | 0.8505   | 0.8957 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

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