WL_DISEASE_NER_v1 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - wl-disease
model-index:
  - name: WL_DISEASE_NER_v1
    results: []

WL_DISEASE_NER_v1

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

  • Loss: 0.1489
  • Diso Precision: 0.7908
  • Diso Recall: 0.8397
  • Diso F1: 0.8145
  • Diso Number: 1765
  • Overall Precision: 0.7908
  • Overall Recall: 0.8397
  • Overall F1: 0.8145
  • Overall Accuracy: 0.9631

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: 2e-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: 4

Training results

Training Loss Epoch Step Validation Loss Diso Precision Diso Recall Diso F1 Diso Number Overall Precision Overall Recall Overall F1 Overall Accuracy
0.1199 1.0 1714 0.1187 0.7739 0.7972 0.7854 1765 0.7739 0.7972 0.7854 0.9610
0.0916 2.0 3428 0.1237 0.7748 0.8266 0.7999 1765 0.7748 0.8266 0.7999 0.9620
0.0625 3.0 5142 0.1343 0.7900 0.8289 0.8090 1765 0.7900 0.8289 0.8090 0.9630
0.0485 4.0 6856 0.1489 0.7908 0.8397 0.8145 1765 0.7908 0.8397 0.8145 0.9631

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2