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luisgasco/biomedical-roberta-finetuned-iomed_task_b4_ep13
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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: 1.0160
  • Precision: 0.1934
  • Recall: 0.3953
  • F1: 0.2597
  • Accuracy: 0.7681

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: 2.2e-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: 13

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
2.1178 1.3 988 1.3039 0.0802 0.2102 0.1161 0.7321
1.2448 2.6 1976 1.1444 0.1161 0.2811 0.1643 0.7568
1.0297 3.9 2964 1.0724 0.1484 0.3299 0.2047 0.7658
0.9496 5.2 3952 1.0342 0.1676 0.3583 0.2284 0.7685
0.88 6.5 4940 1.0465 0.1805 0.3795 0.2446 0.7660
0.8168 7.8 5928 1.0253 0.1713 0.3638 0.2329 0.7624
0.7863 9.1 6916 1.0293 0.1754 0.3622 0.2364 0.7641
0.784 10.4 7904 1.0159 0.1920 0.3890 0.2571 0.7648
0.7161 11.7 8892 1.0121 0.1853 0.3819 0.2495 0.7654
0.7629 13.0 9880 1.0160 0.1934 0.3953 0.2597 0.7681

Framework versions

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