beto-finetuned-fact
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the fact2020 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0422
- Precision: 0.9949
- Recall: 0.9895
- F1: 0.9900
- Accuracy: 0.9895
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 116 | 0.0437 | 0.9943 | 0.9883 | 0.9889 | 0.9883 |
No log | 2.0 | 232 | 0.0432 | 0.9949 | 0.9894 | 0.9900 | 0.9894 |
No log | 3.0 | 348 | 0.0422 | 0.9949 | 0.9895 | 0.9900 | 0.9895 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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Base model
dccuchile/bert-base-spanish-wwm-casedEvaluation results
- Precision on fact2020validation set self-reported0.995
- Recall on fact2020validation set self-reported0.989
- F1 on fact2020validation set self-reported0.990
- Accuracy on fact2020validation set self-reported0.989