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# training

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: 2.3256
- Accuracy: 0.6768
- F1: 0.6764
- Precision: 0.6772
- Recall: 0.6768

## 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: 40
- eval_batch_size: 20
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 66   | 0.7029          | 0.4939   | 0.3623 | 0.4289    | 0.4939 |
| No log        | 2.0   | 132  | 0.6985          | 0.4726   | 0.4074 | 0.4429    | 0.4726 |
| No log        | 3.0   | 198  | 0.7052          | 0.5091   | 0.5079 | 0.5101    | 0.5091 |
| No log        | 4.0   | 264  | 0.7277          | 0.5732   | 0.5687 | 0.5746    | 0.5732 |
| No log        | 5.0   | 330  | 0.8226          | 0.5747   | 0.5711 | 0.5791    | 0.5747 |
| No log        | 6.0   | 396  | 0.9070          | 0.6098   | 0.6084 | 0.6126    | 0.6098 |
| No log        | 7.0   | 462  | 0.9877          | 0.6296   | 0.6288 | 0.6299    | 0.6296 |
| 0.4904        | 8.0   | 528  | 1.2868          | 0.5976   | 0.5814 | 0.6198    | 0.5976 |
| 0.4904        | 9.0   | 594  | 1.2709          | 0.6433   | 0.6396 | 0.6517    | 0.6433 |
| 0.4904        | 10.0  | 660  | 1.3541          | 0.6494   | 0.6494 | 0.6494    | 0.6494 |
| 0.4904        | 11.0  | 726  | 1.4138          | 0.6631   | 0.6572 | 0.6724    | 0.6631 |
| 0.4904        | 12.0  | 792  | 1.5116          | 0.6631   | 0.6616 | 0.6676    | 0.6631 |
| 0.4904        | 13.0  | 858  | 1.5349          | 0.6738   | 0.6687 | 0.6825    | 0.6738 |
| 0.4904        | 14.0  | 924  | 1.5437          | 0.6845   | 0.6845 | 0.6845    | 0.6845 |
| 0.4904        | 15.0  | 990  | 1.8465          | 0.6585   | 0.6581 | 0.6588    | 0.6585 |
| 0.0493        | 16.0  | 1056 | 1.8186          | 0.6662   | 0.6661 | 0.6667    | 0.6662 |
| 0.0493        | 17.0  | 1122 | 1.9234          | 0.6601   | 0.6589 | 0.6635    | 0.6601 |
| 0.0493        | 18.0  | 1188 | 1.9517          | 0.6707   | 0.6689 | 0.6763    | 0.6707 |
| 0.0493        | 19.0  | 1254 | 1.9673          | 0.6616   | 0.6609 | 0.6639    | 0.6616 |
| 0.0493        | 20.0  | 1320 | 2.0034          | 0.6768   | 0.6768 | 0.6769    | 0.6768 |
| 0.0493        | 21.0  | 1386 | 2.0452          | 0.6707   | 0.6707 | 0.6707    | 0.6707 |
| 0.0493        | 22.0  | 1452 | 2.1151          | 0.6570   | 0.6569 | 0.6578    | 0.6570 |
| 0.0085        | 23.0  | 1518 | 2.0888          | 0.6631   | 0.6627 | 0.6633    | 0.6631 |
| 0.0085        | 24.0  | 1584 | 2.1101          | 0.6646   | 0.6646 | 0.6649    | 0.6646 |
| 0.0085        | 25.0  | 1650 | 2.1330          | 0.6662   | 0.6661 | 0.6666    | 0.6662 |
| 0.0085        | 26.0  | 1716 | 2.1890          | 0.6662   | 0.6659 | 0.6663    | 0.6662 |
| 0.0085        | 27.0  | 1782 | 2.2275          | 0.6601   | 0.6598 | 0.6602    | 0.6601 |
| 0.0085        | 28.0  | 1848 | 2.2380          | 0.6662   | 0.6648 | 0.6704    | 0.6662 |
| 0.0085        | 29.0  | 1914 | 2.2606          | 0.6646   | 0.6646 | 0.6650    | 0.6646 |
| 0.0085        | 30.0  | 1980 | 2.2708          | 0.6738   | 0.6734 | 0.6755    | 0.6738 |
| 0.0029        | 31.0  | 2046 | 2.2827          | 0.6677   | 0.6675 | 0.6677    | 0.6677 |
| 0.0029        | 32.0  | 2112 | 2.2992          | 0.6738   | 0.6738 | 0.6738    | 0.6738 |
| 0.0029        | 33.0  | 2178 | 2.2926          | 0.6768   | 0.6757 | 0.6782    | 0.6768 |
| 0.0029        | 34.0  | 2244 | 2.3100          | 0.6738   | 0.6738 | 0.6740    | 0.6738 |
| 0.0029        | 35.0  | 2310 | 2.3081          | 0.6768   | 0.6767 | 0.6768    | 0.6768 |
| 0.0029        | 36.0  | 2376 | 2.3080          | 0.6768   | 0.6764 | 0.6772    | 0.6768 |
| 0.0029        | 37.0  | 2442 | 2.3242          | 0.6784   | 0.6783 | 0.6787    | 0.6784 |
| 0.0004        | 38.0  | 2508 | 2.3252          | 0.6799   | 0.6799 | 0.6799    | 0.6799 |
| 0.0004        | 39.0  | 2574 | 2.3228          | 0.6784   | 0.6782 | 0.6784    | 0.6784 |
| 0.0004        | 40.0  | 2640 | 2.3256          | 0.6768   | 0.6764 | 0.6772    | 0.6768 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

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