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--- |
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license: mit |
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base_model: xlnet/xlnet-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: xlnet-base-cased-airlines-news-multi-label |
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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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# xlnet-base-cased-airlines-news-multi-label |
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This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/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: 0.2822 |
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- F1: 0.6647 |
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- Roc Auc: 0.8080 |
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- Accuracy: 0.6116 |
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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: 12 |
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- eval_batch_size: 12 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 150 | 0.2088 | 0.5979 | 0.7399 | 0.6027 | |
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| No log | 2.0 | 300 | 0.1928 | 0.6596 | 0.7725 | 0.6562 | |
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| No log | 3.0 | 450 | 0.2049 | 0.6327 | 0.7653 | 0.5982 | |
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| 0.2167 | 4.0 | 600 | 0.2226 | 0.6506 | 0.8007 | 0.6027 | |
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| 0.2167 | 5.0 | 750 | 0.2280 | 0.6288 | 0.7666 | 0.5893 | |
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| 0.2167 | 6.0 | 900 | 0.2418 | 0.6295 | 0.7709 | 0.5938 | |
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| 0.0812 | 7.0 | 1050 | 0.2610 | 0.6258 | 0.7722 | 0.5982 | |
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| 0.0812 | 8.0 | 1200 | 0.2756 | 0.6098 | 0.7606 | 0.5804 | |
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| 0.0812 | 9.0 | 1350 | 0.2822 | 0.6647 | 0.8080 | 0.6116 | |
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| 0.0325 | 10.0 | 1500 | 0.2908 | 0.6378 | 0.7873 | 0.5938 | |
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| 0.0325 | 11.0 | 1650 | 0.3050 | 0.6319 | 0.7860 | 0.5938 | |
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| 0.0325 | 12.0 | 1800 | 0.3044 | 0.6277 | 0.7830 | 0.5804 | |
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| 0.0325 | 13.0 | 1950 | 0.3030 | 0.6254 | 0.7804 | 0.5804 | |
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| 0.015 | 14.0 | 2100 | 0.3057 | 0.6319 | 0.7860 | 0.5848 | |
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| 0.015 | 15.0 | 2250 | 0.3013 | 0.6168 | 0.7744 | 0.5670 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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