LP-NLI Models
Collection
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Updated
bert-xnli-es-classifier
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the xnli dataset. It achieves the following results on the evaluation set:
- Loss: 0.5109
- Accuracy: 0.8277
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4401 | 1.0 | 6136 | 0.4733 | 0.8116 |
| 0.4245 | 2.0 | 12272 | 0.4667 | 0.8309 |
| 0.29 | 3.0 | 18408 | 0.5109 | 0.8277 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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