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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_1_binary |
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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_1_binary |
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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: 1.7607 |
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- F1: 0.7778 |
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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 | 0.4111 | 0.7555 | |
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| 0.4387 | 2.0 | 576 | 0.4075 | 0.7540 | |
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| 0.4387 | 3.0 | 864 | 0.5344 | 0.7567 | |
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| 0.2471 | 4.0 | 1152 | 0.7405 | 0.7597 | |
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| 0.2471 | 5.0 | 1440 | 1.0564 | 0.7508 | |
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| 0.1419 | 6.0 | 1728 | 1.0703 | 0.7751 | |
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| 0.0845 | 7.0 | 2016 | 1.0866 | 0.7609 | |
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| 0.0845 | 8.0 | 2304 | 1.2135 | 0.7751 | |
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| 0.05 | 9.0 | 2592 | 1.3649 | 0.7516 | |
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| 0.05 | 10.0 | 2880 | 1.4943 | 0.7590 | |
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| 0.0267 | 11.0 | 3168 | 1.5174 | 0.7412 | |
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| 0.0267 | 12.0 | 3456 | 1.4884 | 0.7559 | |
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| 0.0278 | 13.0 | 3744 | 1.5109 | 0.7405 | |
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| 0.0201 | 14.0 | 4032 | 1.7251 | 0.7409 | |
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| 0.0201 | 15.0 | 4320 | 1.5833 | 0.7354 | |
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| 0.0185 | 16.0 | 4608 | 1.7744 | 0.7598 | |
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| 0.0185 | 17.0 | 4896 | 1.8283 | 0.7619 | |
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| 0.0066 | 18.0 | 5184 | 1.7607 | 0.7778 | |
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| 0.0066 | 19.0 | 5472 | 1.7503 | 0.7719 | |
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| 0.0078 | 20.0 | 5760 | 1.7807 | 0.7508 | |
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| 0.006 | 21.0 | 6048 | 1.6887 | 0.7629 | |
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| 0.006 | 22.0 | 6336 | 1.7041 | 0.7678 | |
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| 0.0074 | 23.0 | 6624 | 1.7337 | 0.7633 | |
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| 0.0074 | 24.0 | 6912 | 1.7548 | 0.7645 | |
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| 0.0035 | 25.0 | 7200 | 1.7685 | 0.7621 | |
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### Framework versions |
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- Transformers 4.21.0 |
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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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