Finetuning_XLNET_Paraphrase_Classification
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: 0.9155
- Accuracy: 0.8701
- F1: 0.8671
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5517 | 1.0 | 619 | 0.3508 | 0.8529 | 0.8513 |
| 0.3345 | 2.0 | 1238 | 0.4829 | 0.8725 | 0.8711 |
| 0.2295 | 3.0 | 1857 | 0.9169 | 0.8627 | 0.8585 |
| 0.1313 | 4.0 | 2476 | 0.8408 | 0.8652 | 0.8624 |
| 0.0398 | 5.0 | 3095 | 0.9155 | 0.8701 | 0.8671 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for ahmed792002/Finetuning_XLNET_Paraphrase_Classification
Base model
xlnet/xlnet-base-cased