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--- |
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license: mit |
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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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model-index: |
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- name: xlnet-base-cased_fold_10_binary_v1 |
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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_fold_10_binary_v1 |
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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: 1.7782 |
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- F1: 0.8137 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 288 | 0.3796 | 0.8145 | |
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| 0.4196 | 2.0 | 576 | 0.4319 | 0.7810 | |
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| 0.4196 | 3.0 | 864 | 0.6227 | 0.8002 | |
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| 0.231 | 4.0 | 1152 | 0.6258 | 0.7941 | |
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| 0.231 | 5.0 | 1440 | 1.0692 | 0.7866 | |
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| 0.1307 | 6.0 | 1728 | 1.1257 | 0.8005 | |
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| 0.0756 | 7.0 | 2016 | 1.2283 | 0.8072 | |
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| 0.0756 | 8.0 | 2304 | 1.3407 | 0.8061 | |
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| 0.0486 | 9.0 | 2592 | 1.5232 | 0.8059 | |
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| 0.0486 | 10.0 | 2880 | 1.6731 | 0.8053 | |
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| 0.0339 | 11.0 | 3168 | 1.6536 | 0.8087 | |
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| 0.0339 | 12.0 | 3456 | 1.7526 | 0.7996 | |
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| 0.019 | 13.0 | 3744 | 1.6662 | 0.7909 | |
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| 0.0237 | 14.0 | 4032 | 1.6028 | 0.8071 | |
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| 0.0237 | 15.0 | 4320 | 1.7627 | 0.7964 | |
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| 0.0078 | 16.0 | 4608 | 1.6513 | 0.8169 | |
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| 0.0078 | 17.0 | 4896 | 1.7795 | 0.8039 | |
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| 0.015 | 18.0 | 5184 | 1.8669 | 0.7935 | |
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| 0.015 | 19.0 | 5472 | 1.6288 | 0.8118 | |
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| 0.0124 | 20.0 | 5760 | 1.6630 | 0.8104 | |
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| 0.004 | 21.0 | 6048 | 1.7418 | 0.8167 | |
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| 0.004 | 22.0 | 6336 | 1.7651 | 0.8128 | |
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| 0.0043 | 23.0 | 6624 | 1.7279 | 0.8163 | |
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| 0.0043 | 24.0 | 6912 | 1.8177 | 0.8093 | |
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| 0.004 | 25.0 | 7200 | 1.7782 | 0.8137 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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