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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_9_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_9_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: 1.7204
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- F1: 0.8203
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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 | 291 | 0.4045 | 0.8001 |
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| 0.4262 | 2.0 | 582 | 0.3914 | 0.8297 |
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| 0.4262 | 3.0 | 873 | 0.5050 | 0.8029 |
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| 0.2488 | 4.0 | 1164 | 0.7681 | 0.8007 |
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| 0.2488 | 5.0 | 1455 | 0.8349 | 0.8262 |
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| 0.1483 | 6.0 | 1746 | 0.9045 | 0.8220 |
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| 0.0894 | 7.0 | 2037 | 1.1584 | 0.8165 |
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| 0.0894 | 8.0 | 2328 | 1.1818 | 0.8300 |
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| 0.0389 | 9.0 | 2619 | 1.3332 | 0.8147 |
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| 0.0389 | 10.0 | 2910 | 1.2373 | 0.8285 |
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| 0.038 | 11.0 | 3201 | 1.3156 | 0.8234 |
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| 0.038 | 12.0 | 3492 | 1.3251 | 0.8341 |
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| 0.0211 | 13.0 | 3783 | 1.3144 | 0.8255 |
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| 0.0158 | 14.0 | 4074 | 1.5686 | 0.8168 |
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| 0.0158 | 15.0 | 4365 | 1.5382 | 0.8185 |
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| 0.0165 | 16.0 | 4656 | 1.5203 | 0.8282 |
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| 0.0165 | 17.0 | 4947 | 1.5352 | 0.8136 |
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| 0.0142 | 18.0 | 5238 | 1.4799 | 0.8243 |
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| 0.0062 | 19.0 | 5529 | 1.5030 | 0.8294 |
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| 0.0062 | 20.0 | 5820 | 1.6264 | 0.8094 |
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| 0.0078 | 21.0 | 6111 | 1.6949 | 0.8122 |
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| 0.0078 | 22.0 | 6402 | 1.7106 | 0.8139 |
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| 0.0043 | 23.0 | 6693 | 1.7234 | 0.8218 |
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| 0.0043 | 24.0 | 6984 | 1.7344 | 0.8208 |
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| 0.0028 | 25.0 | 7275 | 1.7204 | 0.8203 |
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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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