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xlnet-large-cased-detect-dep-v4
This model is a fine-tuned version of xlnet-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5693
- Accuracy: 0.733
- F1: 0.8089
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.6433 | 1.0 | 751 | 0.5590 | 0.718 | 0.8082 |
| 0.603 | 2.0 | 1502 | 0.5566 | 0.746 | 0.8204 |
| 0.5791 | 3.0 | 2253 | 0.5693 | 0.733 | 0.8089 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
