metadata
tags:
- generated_from_trainer
datasets:
- conll2002
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-spanish-wwm-cased-t1
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2002
type: conll2002
config: es
split: validation
args: es
metrics:
- name: Precision
type: precision
value: 0.7979376919701624
- name: Recall
type: recall
value: 0.8357077205882353
- name: F1
type: f1
value: 0.8163860830527497
- name: Accuracy
type: accuracy
value: 0.9686647656831143
bert-base-spanish-wwm-cased-t1
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the conll2002 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1173
- Precision: 0.7979
- Recall: 0.8357
- F1: 0.8164
- Accuracy: 0.9687
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0773 | 1.0 | 1041 | 0.1173 | 0.7979 | 0.8357 | 0.8164 | 0.9687 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2