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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - shared-task
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bsc-bio-ehr-es-finetuned-ner-1
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: shared-task
          type: shared-task
          config: Shared
          split: validation
          args: Shared
        metrics:
          - name: Precision
            type: precision
            value: 0.28507462686567164
          - name: Recall
            type: recall
            value: 0.3560111835973905
          - name: F1
            type: f1
            value: 0.3166183174471612
          - name: Accuracy
            type: accuracy
            value: 0.8444321635810997

bsc-bio-ehr-es-finetuned-ner-1

This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the shared-task dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6021
  • Precision: 0.2851
  • Recall: 0.3560
  • F1: 0.3166
  • Accuracy: 0.8444

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 59 0.6644 0.2234 0.2600 0.2403 0.8198
No log 2.0 118 0.5786 0.1997 0.2507 0.2223 0.8331
No log 3.0 177 0.6083 0.2732 0.3187 0.2942 0.8379
No log 4.0 236 0.6032 0.2855 0.3486 0.3139 0.8366
No log 5.0 295 0.6021 0.2851 0.3560 0.3166 0.8444

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3