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luisgasco/biomedical-roberta-finetuned-iomed_task_b4_ep20
20d6cdd
metadata
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-biomedical-es
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: biomedical-roberta-finetuned-iomed_task
    results: []

biomedical-roberta-finetuned-iomed_task

This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-biomedical-es on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0582
  • Precision: 0.2269
  • Recall: 0.4283
  • F1: 0.2966
  • Accuracy: 0.7695

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: 2.1e-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
1.2536 2.0 1520 1.2135 0.1082 0.2685 0.1542 0.7422
1.0249 4.0 3040 1.0510 0.1448 0.3244 0.2002 0.7650
0.9 6.0 4560 1.0098 0.1587 0.3512 0.2186 0.7694
0.8002 8.0 6080 1.0143 0.1835 0.3795 0.2474 0.7664
0.7195 10.0 7600 1.0173 0.2007 0.4055 0.2685 0.7691
0.693 12.0 9120 1.0218 0.1991 0.4079 0.2676 0.7683
0.6139 14.0 10640 1.0394 0.2063 0.4071 0.2738 0.7672
0.616 16.0 12160 1.0376 0.2141 0.4142 0.2823 0.7695
0.5911 18.0 13680 1.0491 0.2240 0.4268 0.2938 0.7697
0.6042 20.0 15200 1.0582 0.2269 0.4283 0.2966 0.7695

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3