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# NEREL-BIO_RuBERT_base

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the dataset [NEREL-BIO](https://github.com/nerel-ds/NEREL-BIO/tree/master).
It achieves the following results on the evaluation set:
- Loss: 0.0308
- Precision: 0.9854
- Recall: 0.9823
- F1: 0.9839
- Accuracy: 0.9917

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 3.0739        | 0.33  | 50   | 2.3665          | 0.1842    | 0.0870 | 0.1182 | 0.3558   |
| 1.8092        | 0.65  | 100  | 1.1732          | 0.5774    | 0.5137 | 0.5437 | 0.7011   |
| 1.1032        | 0.98  | 150  | 0.8155          | 0.6955    | 0.6546 | 0.6744 | 0.7874   |
| 0.8338        | 1.31  | 200  | 0.6058          | 0.7512    | 0.7176 | 0.7340 | 0.8355   |
| 0.7068        | 1.63  | 250  | 0.4796          | 0.7912    | 0.7627 | 0.7767 | 0.8663   |
| 0.5839        | 1.96  | 300  | 0.4285          | 0.8160    | 0.7910 | 0.8033 | 0.8832   |
| 0.443         | 2.29  | 350  | 0.3589          | 0.8304    | 0.8271 | 0.8287 | 0.8988   |
| 0.4312        | 2.61  | 400  | 0.3072          | 0.8569    | 0.8395 | 0.8481 | 0.9133   |
| 0.3862        | 2.94  | 450  | 0.2802          | 0.8693    | 0.8503 | 0.8597 | 0.9198   |
| 0.29          | 3.27  | 500  | 0.2379          | 0.8874    | 0.8753 | 0.8813 | 0.9324   |
| 0.2896        | 3.59  | 550  | 0.1988          | 0.9030    | 0.8902 | 0.8966 | 0.9425   |
| 0.2785        | 3.92  | 600  | 0.1865          | 0.9078    | 0.8950 | 0.9014 | 0.9458   |
| 0.2053        | 4.25  | 650  | 0.1596          | 0.9232    | 0.9067 | 0.9149 | 0.9533   |
| 0.2044        | 4.58  | 700  | 0.1325          | 0.9371    | 0.9249 | 0.9310 | 0.9621   |
| 0.1868        | 4.9   | 750  | 0.1231          | 0.9419    | 0.9324 | 0.9371 | 0.9657   |
| 0.1284        | 5.23  | 800  | 0.1219          | 0.9423    | 0.9264 | 0.9343 | 0.9650   |
| 0.1448        | 5.56  | 850  | 0.0941          | 0.9561    | 0.9480 | 0.9520 | 0.9740   |
| 0.1346        | 5.88  | 900  | 0.0849          | 0.9586    | 0.9493 | 0.9539 | 0.9758   |
| 0.1013        | 6.21  | 950  | 0.0713          | 0.9657    | 0.9568 | 0.9612 | 0.9802   |
| 0.0917        | 6.54  | 1000 | 0.0652          | 0.9688    | 0.9601 | 0.9644 | 0.9816   |
| 0.0961        | 6.86  | 1050 | 0.0571          | 0.9727    | 0.9669 | 0.9698 | 0.9844   |
| 0.074         | 7.19  | 1100 | 0.0521          | 0.9752    | 0.9704 | 0.9728 | 0.9857   |
| 0.0758        | 7.52  | 1150 | 0.0480          | 0.9771    | 0.9712 | 0.9741 | 0.9866   |
| 0.0681        | 7.84  | 1200 | 0.0409          | 0.9802    | 0.9746 | 0.9774 | 0.9885   |
| 0.0557        | 8.17  | 1250 | 0.0364          | 0.9822    | 0.9786 | 0.9804 | 0.9899   |
| 0.0431        | 8.5   | 1300 | 0.0343          | 0.9833    | 0.9796 | 0.9814 | 0.9907   |
| 0.05          | 8.82  | 1350 | 0.0323          | 0.9847    | 0.9818 | 0.9832 | 0.9914   |
| 0.0434        | 9.15  | 1400 | 0.0314          | 0.9851    | 0.9820 | 0.9835 | 0.9915   |
| 0.0425        | 9.48  | 1450 | 0.0309          | 0.9854    | 0.9824 | 0.9839 | 0.9917   |
| 0.0483        | 9.8   | 1500 | 0.0308          | 0.9854    | 0.9823 | 0.9839 | 0.9917   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "DeepPavlov/rubert-base-cased", "model-index": [{"name": "NEREL-BIO_RuBERT_base", "results": []}]}
transformers safetensors bert token-classification generated_from_trainer base_model:DeepPavlov/rubert-base-cased autotrain_compatible endpoints_compatible region:us