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--- |
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library_name: transformers |
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license: mit |
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base_model: xlnet-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: Finetuning_XLNET_Paraphrase_Classification |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Finetuning_XLNET_Paraphrase_Classification |
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9155 |
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- Accuracy: 0.8701 |
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- F1: 0.8671 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.5517 | 1.0 | 619 | 0.3508 | 0.8529 | 0.8513 | |
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| 0.3345 | 2.0 | 1238 | 0.4829 | 0.8725 | 0.8711 | |
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| 0.2295 | 3.0 | 1857 | 0.9169 | 0.8627 | 0.8585 | |
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| 0.1313 | 4.0 | 2476 | 0.8408 | 0.8652 | 0.8624 | |
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| 0.0398 | 5.0 | 3095 | 0.9155 | 0.8701 | 0.8671 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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