roberta-bne-fine-tuned-text-classification-SL-1200samples
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5536
- F1: 0.4587
- Recall: 0.4697
- Accuracy: 0.4697
- Precision: 0.4773
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: 0.0001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
---|---|---|---|---|---|---|---|
2.3608 | 1.0 | 1503 | 2.2771 | 0.3955 | 0.4385 | 0.4385 | 0.4415 |
1.9673 | 2.0 | 3006 | 2.0774 | 0.4439 | 0.4769 | 0.4769 | 0.4716 |
1.5479 | 3.0 | 4509 | 2.1167 | 0.4567 | 0.4767 | 0.4767 | 0.4719 |
1.0917 | 4.0 | 6012 | 2.4366 | 0.4512 | 0.4451 | 0.4451 | 0.4902 |
0.8063 | 5.0 | 7515 | 2.5536 | 0.4587 | 0.4697 | 0.4697 | 0.4773 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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