metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: >-
      NLP-CIC-WFU_SocialDisNER_fine_tuned_NER_EHR_Spanish_model_Mulitlingual_BERT_v2
    results: []
widget:
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  - text: >-
      Tuitea con #gotasdesolidaridad y brindemos nuestro apoyo a los pacientes y
      familiares en el cáncer de mamá @Solan_de_Cabras Uniros a compartirlo
      @azuchristeamo y @luismi12c https://t.co/TgQizz2kpT

NLP-CIC-WFU_SocialDisNER_fine_tuned_NER_EHR_Spanish_model_Mulitlingual_BERT_v2

This model is a fine-tuned version of ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1483
Precision: 0.8699
Recall: 0.8722
F1: 0.8711
Accuracy: 0.9771

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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	467	0.0851	0.8415	0.8209	0.8310	0.9720
0.1011	2.0	934	0.1034	0.8681	0.8464	0.8571	0.9744
0.0537	3.0	1401	0.1094	0.8527	0.8608	0.8568	0.9753
0.0335	4.0	1868	0.1239	0.8617	0.8603	0.8610	0.9751
0.0185	5.0	2335	0.1192	0.8689	0.8627	0.8658	0.9756
0.0112	6.0	2802	0.1426	0.8672	0.8663	0.8667	0.9765
0.0067	7.0	3269	0.1483	0.8699	0.8722	0.8711	0.9771

Framework versions

Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1