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# bert-base-uncased-glue-mrpc-camilovg

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue and the mrpc datasets.
It achieves the following results on the evaluation set:
- Loss: 0.3969
- Accuracy: 0.8529
- F1: 0.8929

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5207        | 1.09  | 500  | 0.3969          | 0.8529   | 0.8929 |
| 0.2963        | 2.18  | 1000 | 0.5402          | 0.8725   | 0.9110 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["text-classification", "generated_from_trainer"], "datasets": ["glue"], "metrics": ["accuracy", "f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-glue-mrpc-camilovg", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "glue", "type": "glue", "config": "mrpc", "split": "validation", "args": "mrpc"}, "metrics": [{"type": "accuracy", "value": 0.8529411764705882, "name": "Accuracy"}, {"type": "f1", "value": 0.8928571428571429, "name": "F1"}]}]}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:glue base_model:bert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us