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# dnrti_our

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2893
- Precision: 0.5617
- Recall: 0.5754
- F1: 0.5685
- Accuracy: 0.9214

## 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: 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: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.6248        | 0.59  | 500  | 0.3242          | 0.5148    | 0.5422 | 0.5281 | 0.9182   |
| 0.3048        | 1.19  | 1000 | 0.2893          | 0.5617    | 0.5754 | 0.5685 | 0.9214   |
| 0.2449        | 1.78  | 1500 | 0.3179          | 0.5095    | 0.6171 | 0.5582 | 0.9148   |
| 0.2088        | 2.37  | 2000 | 0.3358          | 0.5238    | 0.6368 | 0.5748 | 0.9099   |
| 0.1788        | 2.97  | 2500 | 0.3198          | 0.5496    | 0.6802 | 0.6080 | 0.9181   |
| 0.1433        | 3.56  | 3000 | 0.3423          | 0.5565    | 0.6491 | 0.5992 | 0.9179   |
| 0.1381        | 4.15  | 3500 | 0.3747          | 0.5633    | 0.6225 | 0.5914 | 0.9168   |
| 0.1161        | 4.74  | 4000 | 0.4113          | 0.5169    | 0.6542 | 0.5775 | 0.9093   |
| 0.1002        | 5.34  | 4500 | 0.3938          | 0.5487    | 0.6431 | 0.5921 | 0.9150   |
| 0.0954        | 5.93  | 5000 | 0.3862          | 0.5612    | 0.6482 | 0.6016 | 0.9192   |
| 0.0762        | 6.52  | 5500 | 0.4267          | 0.5576    | 0.6416 | 0.5967 | 0.9169   |
| 0.0741        | 7.12  | 6000 | 0.4455          | 0.5693    | 0.6434 | 0.6041 | 0.9184   |
| 0.064         | 7.71  | 6500 | 0.4512          | 0.5672    | 0.6368 | 0.6000 | 0.9177   |
| 0.0567        | 8.3   | 7000 | 0.4559          | 0.5682    | 0.6269 | 0.5962 | 0.9188   |
| 0.0504        | 8.9   | 7500 | 0.4841          | 0.5553    | 0.6422 | 0.5956 | 0.9150   |
| 0.0465        | 9.49  | 8000 | 0.4834          | 0.5606    | 0.6380 | 0.5968 | 0.9169   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "roberta-base", "model-index": [{"name": "dnrti_our", "results": []}]}
transformers tensorboard safetensors roberta token-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible region:us