---
license: apache-2.0
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
tags:
- token-classification
- generated_from_trainer
datasets:
- Rodrigo1771/multi-train-drugtemist-dev-ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: output
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: Rodrigo1771/multi-train-drugtemist-dev-ner
      type: Rodrigo1771/multi-train-drugtemist-dev-ner
      config: MultiTrainDrugTEMISTDevNER
      split: validation
      args: MultiTrainDrugTEMISTDevNER
    metrics:
    - name: Precision
      type: precision
      value: 0.09691960931630353
    - name: Recall
      type: recall
      value: 0.9485294117647058
    - name: F1
      type: f1
      value: 0.17586912065439672
    - name: Accuracy
      type: accuracy
      value: 0.8099635429897495
---

<!-- 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. -->

# output

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 Rodrigo1771/multi-train-drugtemist-dev-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6631
- Precision: 0.0969
- Recall: 0.9485
- F1: 0.1759
- Accuracy: 0.8100

## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2596        | 0.9997 | 1701  | 0.7913          | 0.0793    | 0.9366 | 0.1462 | 0.7672   |
| 0.1853        | 2.0    | 3403  | 0.6631          | 0.0969    | 0.9485 | 0.1759 | 0.8100   |
| 0.1254        | 2.9997 | 5104  | 1.0729          | 0.0906    | 0.9421 | 0.1653 | 0.7755   |
| 0.0823        | 4.0    | 6806  | 1.2568          | 0.0888    | 0.9504 | 0.1624 | 0.7719   |
| 0.0597        | 4.9997 | 8507  | 1.1908          | 0.0941    | 0.9375 | 0.1710 | 0.7837   |
| 0.0446        | 6.0    | 10209 | 1.3844          | 0.0944    | 0.9504 | 0.1718 | 0.7812   |
| 0.0325        | 6.9997 | 11910 | 1.5515          | 0.0937    | 0.9476 | 0.1705 | 0.7866   |
| 0.022         | 8.0    | 13612 | 1.6300          | 0.0926    | 0.9559 | 0.1689 | 0.7843   |
| 0.017         | 8.9997 | 15313 | 1.7459          | 0.0929    | 0.9531 | 0.1693 | 0.7845   |
| 0.0135        | 9.9971 | 17010 | 1.7861          | 0.0927    | 0.9522 | 0.1690 | 0.7846   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1