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: beto-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: 0.9479897894065092
- name: Recall
type: recall
value: 0.9685937839600087
- name: F1
type: f1
value: 0.9581810363362717
- name: Accuracy
type: accuracy
value: 0.9781675579322638
beto-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: 0.1032
- Precision: 0.9480
- Recall: 0.9686
- F1: 0.9582
- Accuracy: 0.9782
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: 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 |
|---|---|---|---|---|---|---|---|
| 0.3605 | 1.0 | 612 | 0.1104 | 0.9414 | 0.9462 | 0.9438 | 0.9707 |
| 0.1106 | 2.0 | 1224 | 0.1074 | 0.9306 | 0.9707 | 0.9502 | 0.9742 |
| 0.0786 | 3.0 | 1836 | 0.0983 | 0.9460 | 0.9688 | 0.9573 | 0.9776 |
| 0.0596 | 4.0 | 2448 | 0.1017 | 0.9465 | 0.9703 | 0.9583 | 0.9780 |
| 0.0387 | 5.0 | 3060 | 0.1032 | 0.9480 | 0.9686 | 0.9582 | 0.9782 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3