---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wl-disease
model-index:
- name: WL_DISEASE_NER_v1
  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. -->

# WL_DISEASE_NER_v1

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the wl-disease dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1489
- Diso Precision: 0.7908
- Diso Recall: 0.8397
- Diso F1: 0.8145
- Diso Number: 1765
- Overall Precision: 0.7908
- Overall Recall: 0.8397
- Overall F1: 0.8145
- Overall Accuracy: 0.9631

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.1199        | 1.0   | 1714 | 0.1187          | 0.7739         | 0.7972      | 0.7854  | 1765        | 0.7739            | 0.7972         | 0.7854     | 0.9610           |
| 0.0916        | 2.0   | 3428 | 0.1237          | 0.7748         | 0.8266      | 0.7999  | 1765        | 0.7748            | 0.8266         | 0.7999     | 0.9620           |
| 0.0625        | 3.0   | 5142 | 0.1343          | 0.7900         | 0.8289      | 0.8090  | 1765        | 0.7900            | 0.8289         | 0.8090     | 0.9630           |
| 0.0485        | 4.0   | 6856 | 0.1489          | 0.7908         | 0.8397      | 0.8145  | 1765        | 0.7908            | 0.8397         | 0.8145     | 0.9631           |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2