transformers pytorch tensorboard roberta token-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: testlink-class
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# testlink-class

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1523
- Precision: 0.6630
- Recall: 0.7135
- F1: 0.6873
- Accuracy: 0.9745

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 29   | 0.2337          | 0.0       | 0.0    | 0.0    | 0.9440   |
| No log        | 2.0   | 58   | 0.2138          | 0.2632    | 0.0585 | 0.0957 | 0.9526   |
| No log        | 3.0   | 87   | 0.1586          | 0.3824    | 0.1520 | 0.2176 | 0.9557   |
| No log        | 4.0   | 116  | 0.1321          | 0.4444    | 0.2807 | 0.3441 | 0.9635   |
| No log        | 5.0   | 145  | 0.1264          | 0.4422    | 0.3801 | 0.4088 | 0.9629   |
| No log        | 6.0   | 174  | 0.1228          | 0.5224    | 0.4094 | 0.4590 | 0.9679   |
| No log        | 7.0   | 203  | 0.1117          | 0.5706    | 0.5906 | 0.5805 | 0.9690   |
| No log        | 8.0   | 232  | 0.1190          | 0.4832    | 0.6725 | 0.5623 | 0.9658   |
| No log        | 9.0   | 261  | 0.1130          | 0.6022    | 0.6374 | 0.6193 | 0.9712   |
| No log        | 10.0  | 290  | 0.1230          | 0.6032    | 0.6667 | 0.6333 | 0.9715   |
| No log        | 11.0  | 319  | 0.1264          | 0.6122    | 0.7018 | 0.6540 | 0.9712   |
| No log        | 12.0  | 348  | 0.1370          | 0.5224    | 0.7485 | 0.6154 | 0.9657   |
| No log        | 13.0  | 377  | 0.1259          | 0.6122    | 0.7018 | 0.6540 | 0.9726   |
| No log        | 14.0  | 406  | 0.1375          | 0.5447    | 0.7485 | 0.6305 | 0.9692   |
| No log        | 15.0  | 435  | 0.1379          | 0.6384    | 0.6608 | 0.6494 | 0.9728   |
| No log        | 16.0  | 464  | 0.1398          | 0.5865    | 0.7135 | 0.6438 | 0.9715   |
| No log        | 17.0  | 493  | 0.1470          | 0.5775    | 0.7193 | 0.6406 | 0.9706   |
| 0.086         | 18.0  | 522  | 0.1576          | 0.5446    | 0.7135 | 0.6177 | 0.9684   |
| 0.086         | 19.0  | 551  | 0.1489          | 0.6354    | 0.6725 | 0.6534 | 0.9725   |
| 0.086         | 20.0  | 580  | 0.1544          | 0.6591    | 0.6784 | 0.6686 | 0.9730   |
| 0.086         | 21.0  | 609  | 0.1489          | 0.6349    | 0.7018 | 0.6667 | 0.9734   |
| 0.086         | 22.0  | 638  | 0.1488          | 0.6821    | 0.6901 | 0.6860 | 0.9747   |
| 0.086         | 23.0  | 667  | 0.1523          | 0.5953    | 0.7485 | 0.6632 | 0.9717   |
| 0.086         | 24.0  | 696  | 0.1475          | 0.6543    | 0.7193 | 0.6852 | 0.9747   |
| 0.086         | 25.0  | 725  | 0.1507          | 0.6740    | 0.7135 | 0.6932 | 0.9752   |
| 0.086         | 26.0  | 754  | 0.1518          | 0.6703    | 0.7135 | 0.6912 | 0.9745   |
| 0.086         | 27.0  | 783  | 0.1517          | 0.6893    | 0.7135 | 0.7011 | 0.9754   |
| 0.086         | 28.0  | 812  | 0.1521          | 0.6524    | 0.7135 | 0.6816 | 0.9739   |
| 0.086         | 29.0  | 841  | 0.1521          | 0.6595    | 0.7135 | 0.6854 | 0.9743   |
| 0.086         | 30.0  | 870  | 0.1523          | 0.6630    | 0.7135 | 0.6873 | 0.9745   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
