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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-2
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. -->
# ner-2
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: 0.1804
- Precision: 0.6443
- Recall: 0.5708
- F1: 0.6053
- Accuracy: 0.9691
## 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: 7e-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 | 0.2727 | 0.0 | 0.0 | 0.0 | 0.9392 |
| No log | 2.0 | 58 | 0.2246 | 0.1163 | 0.0228 | 0.0382 | 0.9383 |
| No log | 3.0 | 87 | 0.1744 | 0.3718 | 0.1324 | 0.1953 | 0.9480 |
| No log | 4.0 | 116 | 0.1492 | 0.4734 | 0.3653 | 0.4124 | 0.9569 |
| No log | 5.0 | 145 | 0.1472 | 0.4905 | 0.4703 | 0.4802 | 0.9581 |
| No log | 6.0 | 174 | 0.1320 | 0.5403 | 0.5205 | 0.5302 | 0.9618 |
| No log | 7.0 | 203 | 0.1423 | 0.5922 | 0.5571 | 0.5741 | 0.9667 |
| No log | 8.0 | 232 | 0.1616 | 0.5838 | 0.5251 | 0.5529 | 0.9648 |
| No log | 9.0 | 261 | 0.1443 | 0.6082 | 0.5388 | 0.5714 | 0.9676 |
| No log | 10.0 | 290 | 0.1681 | 0.5990 | 0.5662 | 0.5822 | 0.9654 |
| No log | 11.0 | 319 | 0.1611 | 0.4853 | 0.6027 | 0.5377 | 0.9599 |
| No log | 12.0 | 348 | 0.1751 | 0.4887 | 0.5936 | 0.5361 | 0.9588 |
| No log | 13.0 | 377 | 0.1796 | 0.4819 | 0.6073 | 0.5374 | 0.9593 |
| No log | 14.0 | 406 | 0.1609 | 0.6760 | 0.5525 | 0.6080 | 0.9699 |
| No log | 15.0 | 435 | 0.1821 | 0.5136 | 0.6027 | 0.5546 | 0.9606 |
| No log | 16.0 | 464 | 0.1581 | 0.6462 | 0.5753 | 0.6087 | 0.9691 |
| No log | 17.0 | 493 | 0.1582 | 0.6531 | 0.5845 | 0.6169 | 0.9692 |
| 0.0763 | 18.0 | 522 | 0.1641 | 0.5574 | 0.6210 | 0.5875 | 0.9648 |
| 0.0763 | 19.0 | 551 | 0.1681 | 0.5671 | 0.5982 | 0.5822 | 0.9663 |
| 0.0763 | 20.0 | 580 | 0.1710 | 0.5917 | 0.5890 | 0.5904 | 0.9667 |
| 0.0763 | 21.0 | 609 | 0.1794 | 0.6703 | 0.5662 | 0.6139 | 0.9702 |
| 0.0763 | 22.0 | 638 | 0.1759 | 0.6103 | 0.5936 | 0.6019 | 0.9672 |
| 0.0763 | 23.0 | 667 | 0.1762 | 0.6298 | 0.5982 | 0.6136 | 0.9687 |
| 0.0763 | 24.0 | 696 | 0.1811 | 0.6176 | 0.5753 | 0.5957 | 0.9681 |
| 0.0763 | 25.0 | 725 | 0.1793 | 0.6337 | 0.5845 | 0.6081 | 0.9696 |
| 0.0763 | 26.0 | 754 | 0.1794 | 0.6796 | 0.5616 | 0.615 | 0.9702 |
| 0.0763 | 27.0 | 783 | 0.1776 | 0.6293 | 0.5890 | 0.6085 | 0.9692 |
| 0.0763 | 28.0 | 812 | 0.1796 | 0.6443 | 0.5708 | 0.6053 | 0.9694 |
| 0.0763 | 29.0 | 841 | 0.1803 | 0.6410 | 0.5708 | 0.6039 | 0.9692 |
| 0.0763 | 30.0 | 870 | 0.1804 | 0.6443 | 0.5708 | 0.6053 | 0.9691 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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