metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wl
metrics:
- precision
- recall
- f1
- accuracy
base_model: plncmm/roberta-clinical-wl-es
model-index:
- name: spanish-clinical-ner
results:
- task:
type: token-classification
name: Token Classification
dataset:
name: wl
type: wl
config: WL
split: train
args: WL
metrics:
- type: precision
value: 0.6868542362104594
name: Precision
- type: recall
value: 0.7348639455782313
name: Recall
- type: f1
value: 0.7100484758853013
name: F1
- type: accuracy
value: 0.8262735659847573
name: Accuracy
spanish-clinical-ner
This model is a fine-tuned version of plncmm/roberta-clinical-wl-es on the wl dataset. It achieves the following results on the evaluation set:
- Loss: 0.6181
- Precision: 0.6869
- Recall: 0.7349
- F1: 0.7100
- Accuracy: 0.8263
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.0283 | 1.0 | 500 | 0.6862 | 0.6690 | 0.6959 | 0.6822 | 0.8091 |
| 0.599 | 2.0 | 1000 | 0.6198 | 0.6856 | 0.7276 | 0.7059 | 0.8252 |
| 0.4973 | 3.0 | 1500 | 0.6181 | 0.6869 | 0.7349 | 0.7100 | 0.8263 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2