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# bert-base-bible2

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the BastianGroundTruth2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 1.0

## 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: 6e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 18
- training_steps: 90
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.553         | 1.06  | 18   | 0.2484          | 1.0      |
| 0.1121        | 2.12  | 36   | 0.0025          | 1.0      |
| 0.0466        | 3.18  | 54   | 0.0008          | 1.0      |
| 0.0142        | 4.24  | 72   | 0.0005          | 1.0      |
| 0.0178        | 5.29  | 90   | 0.0004          | 1.0      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["-"], "metrics": ["accuracy"], "base_model": "bert-base-cased", "model-index": [{"name": "bert-base-bible2", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer dataset:- base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us