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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_8_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_8_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: 1.5333 |
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- F1: 0.8407 |
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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 | 290 | 0.3866 | 0.8172 | |
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| 0.4299 | 2.0 | 580 | 0.4215 | 0.8246 | |
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| 0.4299 | 3.0 | 870 | 0.4765 | 0.8238 | |
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| 0.2564 | 4.0 | 1160 | 0.7283 | 0.8350 | |
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| 0.2564 | 5.0 | 1450 | 0.6825 | 0.8363 | |
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| 0.1553 | 6.0 | 1740 | 0.9637 | 0.8339 | |
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| 0.0893 | 7.0 | 2030 | 1.1392 | 0.8239 | |
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| 0.0893 | 8.0 | 2320 | 1.1868 | 0.8231 | |
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| 0.0538 | 9.0 | 2610 | 1.2180 | 0.8346 | |
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| 0.0538 | 10.0 | 2900 | 1.2353 | 0.8253 | |
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| 0.0386 | 11.0 | 3190 | 1.1883 | 0.8317 | |
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| 0.0386 | 12.0 | 3480 | 1.2786 | 0.8375 | |
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| 0.0289 | 13.0 | 3770 | 1.3725 | 0.8375 | |
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| 0.0146 | 14.0 | 4060 | 1.3171 | 0.8463 | |
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| 0.0146 | 15.0 | 4350 | 1.2323 | 0.8425 | |
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| 0.0182 | 16.0 | 4640 | 1.3169 | 0.8485 | |
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| 0.0182 | 17.0 | 4930 | 1.4424 | 0.8336 | |
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| 0.0125 | 18.0 | 5220 | 1.4336 | 0.8385 | |
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| 0.0102 | 19.0 | 5510 | 1.4888 | 0.8405 | |
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| 0.0102 | 20.0 | 5800 | 1.5227 | 0.8419 | |
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| 0.0035 | 21.0 | 6090 | 1.4994 | 0.8421 | |
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| 0.0035 | 22.0 | 6380 | 1.4845 | 0.8424 | |
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| 0.0047 | 23.0 | 6670 | 1.5006 | 0.8422 | |
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| 0.0047 | 24.0 | 6960 | 1.5468 | 0.8422 | |
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| 0.0042 | 25.0 | 7250 | 1.5333 | 0.8407 | |
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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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