transformers pytorch tensorboard roberta token-classification generated_from_trainer dataset:cantemist-ner license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- cantemist-ner
license: apache-2.0
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: biomedical-roberta-finetuned-cantemist-test
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: cantemist-ner
      type: cantemist-ner
      config: CantemistNer
      split: train
      args: CantemistNer
    metrics:
    - type: f1
      value: 0.8379235519946587
      name: F1
---

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# biomedical-roberta-finetuned-cantemist-test

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es-cantemist) on the cantemist-ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
- F1: 0.8379

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

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0015        | 1.0   | 607  | 0.0597          | 0.8379 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
