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# AugWordNet_BERT_FPB_finetuned_v1

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: 0.4204
- Accuracy: 0.9376
- F1: 0.9376
- Precision: 0.9377
- Recall: 0.9376

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8417        | 1.0   | 91   | 0.7510          | 0.7410   | 0.7376 | 0.7449    | 0.7410 |
| 0.4682        | 2.0   | 182  | 0.3860          | 0.8534   | 0.8540 | 0.8585    | 0.8534 |
| 0.268         | 3.0   | 273  | 0.3011          | 0.8861   | 0.8855 | 0.8873    | 0.8861 |
| 0.1877        | 4.0   | 364  | 0.3048          | 0.8877   | 0.8877 | 0.8883    | 0.8877 |
| 0.1499        | 5.0   | 455  | 0.3375          | 0.8877   | 0.8876 | 0.8945    | 0.8877 |
| 0.1133        | 6.0   | 546  | 0.4436          | 0.8736   | 0.8723 | 0.8806    | 0.8736 |
| 0.1088        | 7.0   | 637  | 0.3466          | 0.8924   | 0.8924 | 0.8927    | 0.8924 |
| 0.0837        | 8.0   | 728  | 0.3562          | 0.9048   | 0.9050 | 0.9055    | 0.9048 |
| 0.0972        | 9.0   | 819  | 0.4039          | 0.9017   | 0.9012 | 0.9049    | 0.9017 |
| 0.0921        | 10.0  | 910  | 0.3287          | 0.9048   | 0.9047 | 0.9047    | 0.9048 |
| 0.0943        | 11.0  | 1001 | 0.4174          | 0.9095   | 0.9093 | 0.9128    | 0.9095 |
| 0.05          | 12.0  | 1092 | 0.3632          | 0.9095   | 0.9088 | 0.9126    | 0.9095 |
| 0.0562        | 13.0  | 1183 | 0.3304          | 0.9345   | 0.9343 | 0.9346    | 0.9345 |
| 0.0174        | 14.0  | 1274 | 0.3997          | 0.9173   | 0.9173 | 0.9173    | 0.9173 |
| 0.0224        | 15.0  | 1365 | 0.3719          | 0.9329   | 0.9330 | 0.9331    | 0.9329 |
| 0.0004        | 16.0  | 1456 | 0.4295          | 0.9345   | 0.9344 | 0.9345    | 0.9345 |
| 0.0103        | 17.0  | 1547 | 0.4351          | 0.9267   | 0.9266 | 0.9269    | 0.9267 |
| 0.0101        | 18.0  | 1638 | 0.3973          | 0.9360   | 0.9360 | 0.9361    | 0.9360 |
| 0.0003        | 19.0  | 1729 | 0.4204          | 0.9376   | 0.9376 | 0.9377    | 0.9376 |
| 0.0008        | 20.0  | 1820 | 0.4218          | 0.9329   | 0.9330 | 0.9331    | 0.9329 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "base_model": "bert-base-uncased", "model-index": [{"name": "AugWordNet_BERT_FPB_finetuned_v1", "results": []}]}
transformers safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us