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# bert-case-16

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3344
- Precision: 0.9051
- Recall: 0.9067
- F1: 0.905
- Accuracy: 0.9067

## 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: 224
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 44   | 0.3317          | 0.8820    | 0.8667 | 0.8611 | 0.8667   |
| No log        | 2.0   | 88   | 0.3046          | 0.8729    | 0.86   | 0.8547 | 0.86     |
| No log        | 3.0   | 132  | 0.2369          | 0.8767    | 0.9133 | 0.8938 | 0.9133   |
| No log        | 4.0   | 176  | 0.3377          | 0.8820    | 0.8667 | 0.8611 | 0.8667   |
| No log        | 5.0   | 220  | 0.1979          | 0.9205    | 0.92   | 0.9155 | 0.92     |
| No log        | 6.0   | 264  | 0.2214          | 0.9369    | 0.9267 | 0.9266 | 0.9267   |
| No log        | 7.0   | 308  | 0.2868          | 0.9161    | 0.9133 | 0.9092 | 0.9133   |
| No log        | 8.0   | 352  | 0.3189          | 0.9103    | 0.9133 | 0.9115 | 0.9133   |
| No log        | 9.0   | 396  | 0.2944          | 0.9107    | 0.9067 | 0.9077 | 0.9067   |
| No log        | 10.0  | 440  | 0.3017          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| No log        | 11.0  | 484  | 0.3142          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| 0.1074        | 12.0  | 528  | 0.3187          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| 0.1074        | 13.0  | 572  | 0.3274          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| 0.1074        | 14.0  | 616  | 0.3301          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| 0.1074        | 15.0  | 660  | 0.3334          | 0.9051    | 0.9067 | 0.905  | 0.9067   |
| 0.1074        | 16.0  | 704  | 0.3344          | 0.9051    | 0.9067 | 0.905  | 0.9067   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-case-16", "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