metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner-clinical-plncmm-large-25
results: []
bert-finetuned-ner-clinical-plncmm-large-25
This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2487
- Precision: 0.7372
- Recall: 0.8035
- F1: 0.7689
- Accuracy: 0.9270
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: 3e-05
- train_batch_size: 18
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 446 | 0.2607 | 0.6701 | 0.7772 | 0.7197 | 0.9113 |
| 0.6128 | 2.0 | 892 | 0.2298 | 0.7266 | 0.7964 | 0.7599 | 0.9254 |
| 0.1927 | 3.0 | 1338 | 0.2487 | 0.7372 | 0.8035 | 0.7689 | 0.9270 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3