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xlnet-base-cased-finetuned-PRC
This model is a fine-tuned version of xlnet-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5563
- Accuracy: 0.8722
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 391 | 0.5250 | 0.8543 |
| 0.6755 | 2.0 | 782 | 0.4992 | 0.8651 |
| 0.378 | 3.0 | 1173 | 0.5368 | 0.8622 |
| 0.2558 | 4.0 | 1564 | 0.5563 | 0.8722 |
| 0.2558 | 5.0 | 1955 | 0.5695 | 0.8719 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
