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update model card README.md
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README.md
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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_4_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_4_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: 1.5724
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- F1: 0.8315
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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 | 289 | 0.4043 | 0.8009 |
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| 0.4373 | 2.0 | 578 | 0.4093 | 0.8260 |
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| 0.4373 | 3.0 | 867 | 0.5084 | 0.8206 |
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| 0.2707 | 4.0 | 1156 | 0.5945 | 0.8087 |
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| 0.2707 | 5.0 | 1445 | 0.6389 | 0.8251 |
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| 0.1691 | 6.0 | 1734 | 0.8131 | 0.8156 |
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| 0.1012 | 7.0 | 2023 | 0.9865 | 0.8190 |
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| 0.1012 | 8.0 | 2312 | 1.1356 | 0.8342 |
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| 0.0506 | 9.0 | 2601 | 1.0624 | 0.8369 |
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| 0.0506 | 10.0 | 2890 | 1.2604 | 0.8255 |
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| 0.0384 | 11.0 | 3179 | 1.2648 | 0.8183 |
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| 0.0384 | 12.0 | 3468 | 1.3763 | 0.8158 |
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| 0.0318 | 13.0 | 3757 | 1.4966 | 0.8217 |
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| 0.0221 | 14.0 | 4046 | 1.3889 | 0.8250 |
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| 0.0221 | 15.0 | 4335 | 1.4014 | 0.8284 |
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| 0.0145 | 16.0 | 4624 | 1.5321 | 0.8289 |
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| 0.0145 | 17.0 | 4913 | 1.4914 | 0.8233 |
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| 0.0172 | 18.0 | 5202 | 1.3946 | 0.8314 |
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| 0.0172 | 19.0 | 5491 | 1.5032 | 0.8269 |
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| 0.0135 | 20.0 | 5780 | 1.5111 | 0.8328 |
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| 0.0087 | 21.0 | 6069 | 1.4899 | 0.8318 |
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| 0.0087 | 22.0 | 6358 | 1.5562 | 0.8311 |
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| 0.0061 | 23.0 | 6647 | 1.5384 | 0.8327 |
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| 0.0061 | 24.0 | 6936 | 1.5798 | 0.8304 |
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| 0.0052 | 25.0 | 7225 | 1.5724 | 0.8315 |
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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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