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# bert-finetuned-sem_eval-english

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: 0.0808
- F1: 0.4747
- Roc Auc: 0.8705
- Accuracy: 0.6863
- Hamming Loss: 0.0246

## 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: 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy | Hamming Loss |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:------------:|
| No log        | 1.0   | 381  | 0.1614          | 0.0450 | 0.6326  | 0.2188   | 0.0506       |
| 0.2203        | 2.0   | 762  | 0.1223          | 0.1837 | 0.7240  | 0.3962   | 0.0394       |
| 0.1234        | 3.0   | 1143 | 0.1005          | 0.3528 | 0.8231  | 0.6038   | 0.0293       |
| 0.0852        | 4.0   | 1524 | 0.0912          | 0.3786 | 0.8317  | 0.6212   | 0.0276       |
| 0.0852        | 5.0   | 1905 | 0.0871          | 0.3947 | 0.8481  | 0.6538   | 0.0267       |
| 0.0623        | 6.0   | 2286 | 0.0859          | 0.4013 | 0.8493  | 0.645    | 0.0269       |
| 0.0485        | 7.0   | 2667 | 0.0828          | 0.4231 | 0.8573  | 0.6575   | 0.0255       |
| 0.0382        | 8.0   | 3048 | 0.0812          | 0.4368 | 0.8598  | 0.6725   | 0.0251       |
| 0.0382        | 9.0   | 3429 | 0.0803          | 0.4538 | 0.8697  | 0.6837   | 0.0244       |
| 0.0321        | 10.0  | 3810 | 0.0817          | 0.4513 | 0.8653  | 0.675    | 0.0249       |
| 0.0267        | 11.0  | 4191 | 0.0819          | 0.4732 | 0.8655  | 0.6737   | 0.0254       |
| 0.023         | 12.0  | 4572 | 0.0815          | 0.4648 | 0.8675  | 0.6825   | 0.0252       |
| 0.023         | 13.0  | 4953 | 0.0808          | 0.4733 | 0.8699  | 0.68     | 0.0249       |
| 0.0211        | 14.0  | 5334 | 0.0808          | 0.4747 | 0.8705  | 0.6863   | 0.0246       |
| 0.0192        | 15.0  | 5715 | 0.0807          | 0.4727 | 0.8717  | 0.6837   | 0.025        |


### 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": ["f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-finetuned-sem_eval-english", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us