metadata
library_name: transformers
base_model: dccuchile/bert-base-spanish-wwm-cased
tags:
- generated_from_trainer
datasets:
- biobert_json
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-cased-finetuned-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: biobert_json
type: biobert_json
config: Biobert_json
split: validation
args: Biobert_json
metrics:
- name: Precision
type: precision
value: 0.9477110233699712
- name: Recall
type: recall
value: 0.9651162790697675
- name: F1
type: f1
value: 0.9563344640068918
- name: Accuracy
type: accuracy
value: 0.9767557932263815
bert-base-spanish-wwm-cased-finetuned-ner
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the biobert_json dataset. It achieves the following results on the evaluation set:
- Loss: 0.1126
- Precision: 0.9477
- Recall: 0.9651
- F1: 0.9563
- Accuracy: 0.9768
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1463 | 1.0 | 1224 | 0.1119 | 0.9393 | 0.9569 | 0.9480 | 0.9726 |
| 0.0951 | 2.0 | 2448 | 0.1077 | 0.9331 | 0.9692 | 0.9508 | 0.9748 |
| 0.0635 | 3.0 | 3672 | 0.1061 | 0.9445 | 0.9696 | 0.9569 | 0.9770 |
| 0.043 | 4.0 | 4896 | 0.1072 | 0.9485 | 0.9676 | 0.9579 | 0.9772 |
| 0.0324 | 5.0 | 6120 | 0.1126 | 0.9477 | 0.9651 | 0.9563 | 0.9768 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3