roberta-base-bne-finetuned-sqac
This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the sqac dataset. It achieves the following results on the evaluation set:
- Loss: 1.2111
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: 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 |
|---|---|---|---|
| 0.9971 | 1.0 | 1196 | 0.8646 |
| 0.482 | 2.0 | 2392 | 0.9334 |
| 0.1652 | 3.0 | 3588 | 1.2111 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
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Model tree for nlp-en-es/roberta-base-bne-finetuned-sqac
Base model
BSC-LT/roberta-base-bne