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# dnrti_deberta

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2586
- Precision: 0.7684
- Recall: 0.7978
- F1: 0.7828
- Accuracy: 0.9373

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5854        | 0.76  | 500  | 0.4097          | 0.5198    | 0.6403 | 0.5738 | 0.8704   |
| 0.3165        | 1.52  | 1000 | 0.3137          | 0.6396    | 0.6891 | 0.6634 | 0.9029   |
| 0.2535        | 2.28  | 1500 | 0.2948          | 0.6330    | 0.7379 | 0.6814 | 0.9087   |
| 0.2034        | 3.04  | 2000 | 0.2660          | 0.7062    | 0.7494 | 0.7272 | 0.9210   |
| 0.1596        | 3.81  | 2500 | 0.2682          | 0.7071    | 0.7729 | 0.7386 | 0.9232   |
| 0.1269        | 4.57  | 3000 | 0.2595          | 0.7285    | 0.7959 | 0.7607 | 0.9292   |
| 0.1122        | 5.33  | 3500 | 0.2642          | 0.7468    | 0.7826 | 0.7643 | 0.9321   |
| 0.0923        | 6.09  | 4000 | 0.2677          | 0.7513    | 0.8070 | 0.7781 | 0.9352   |
| 0.0804        | 6.85  | 4500 | 0.2586          | 0.7684    | 0.7978 | 0.7828 | 0.9373   |
| 0.0687        | 7.61  | 5000 | 0.2791          | 0.7522    | 0.8236 | 0.7863 | 0.9368   |
| 0.0626        | 8.37  | 5500 | 0.2789          | 0.7614    | 0.8204 | 0.7898 | 0.9379   |
| 0.0552        | 9.13  | 6000 | 0.2774          | 0.7674    | 0.8208 | 0.7932 | 0.9405   |
| 0.0488        | 9.89  | 6500 | 0.2808          | 0.7742    | 0.8213 | 0.7970 | 0.9415   |


### 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": "microsoft/deberta-v3-base", "model-index": [{"name": "dnrti_deberta", "results": []}]}
transformers tensorboard safetensors deberta-v2 token-classification generated_from_trainer base_model:microsoft/deberta-v3-base license:mit autotrain_compatible endpoints_compatible region:us