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xlnet-large-cased-stage-2-ver1
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: 0.4128
- Accuracy: 0.8317
- F1: 0.9022
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 |
|---|---|---|---|---|---|
| No log | 1.0 | 469 | 0.4226 | 0.85 | 0.9189 |
| 0.4839 | 2.0 | 938 | 0.3964 | 0.845 | 0.9141 |
| 0.4284 | 3.0 | 1407 | 0.4128 | 0.8317 | 0.9022 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
