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baseline_xlnet-base-cased_epoch2_batch2_lr2e-05_w0.01
This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5189
- Accuracy: 0.8854
- F1: 0.8442
- Precision: 0.8558
- Recall: 0.8328
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7846 | 1.0 | 1575 | 0.6591 | 0.8343 | 0.7453 | 0.872 | 0.6507 |
| 0.536 | 2.0 | 3150 | 0.5189 | 0.8854 | 0.8442 | 0.8558 | 0.8328 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3
