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# bert-large-cased-5kvul-10aug-3nsfw-exp-10ep

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1089
- 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3639        | 1.0   | 597  | 0.1012          | 1.0      |
| 0.3649        | 2.0   | 1194 | 0.1470          | 1.0      |
| 0.3719        | 3.0   | 1791 | 0.1336          | 1.0      |
| 0.3631        | 4.0   | 2388 | 0.1025          | 1.0      |
| 0.3523        | 5.0   | 2985 | 1.1339          | 0.0      |
| 0.3683        | 6.0   | 3582 | 0.1106          | 1.0      |
| 0.3666        | 7.0   | 4179 | 0.1170          | 1.0      |
| 0.354         | 8.0   | 4776 | 0.0958          | 1.0      |
| 0.3485        | 9.0   | 5373 | 0.1042          | 1.0      |
| 0.3571        | 10.0  | 5970 | 0.1089          | 1.0      |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-large-cased", "model-index": [{"name": "bert-large-cased-5kvul-10aug-3nsfw-exp-10ep", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-large-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us