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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_5_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_5_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: 1.7395
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- F1: 0.8206
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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 | 0.4246 | 0.8154 |
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| 0.4211 | 2.0 | 576 | 0.5181 | 0.8063 |
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| 0.4211 | 3.0 | 864 | 0.4939 | 0.8149 |
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| 0.2483 | 4.0 | 1152 | 0.6181 | 0.8227 |
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| 0.2483 | 5.0 | 1440 | 0.9251 | 0.8006 |
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| 0.1512 | 6.0 | 1728 | 0.9639 | 0.8082 |
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| 0.0858 | 7.0 | 2016 | 1.1315 | 0.8074 |
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| 0.0858 | 8.0 | 2304 | 1.1322 | 0.8303 |
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| 0.053 | 9.0 | 2592 | 1.3171 | 0.8017 |
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| 0.053 | 10.0 | 2880 | 1.3729 | 0.8100 |
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| 0.0325 | 11.0 | 3168 | 1.2708 | 0.8252 |
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| 0.0325 | 12.0 | 3456 | 1.5105 | 0.8242 |
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| 0.0203 | 13.0 | 3744 | 1.4902 | 0.8233 |
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| 0.0179 | 14.0 | 4032 | 1.5874 | 0.8194 |
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| 0.0179 | 15.0 | 4320 | 1.5933 | 0.8135 |
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| 0.0174 | 16.0 | 4608 | 1.5908 | 0.8088 |
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| 0.0174 | 17.0 | 4896 | 1.5692 | 0.8249 |
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| 0.0129 | 18.0 | 5184 | 1.6597 | 0.8167 |
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| 0.0129 | 19.0 | 5472 | 1.6009 | 0.8218 |
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| 0.0095 | 20.0 | 5760 | 1.6962 | 0.8225 |
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| 0.0062 | 21.0 | 6048 | 1.7075 | 0.8182 |
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| 0.0062 | 22.0 | 6336 | 1.7335 | 0.8181 |
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| 0.0077 | 23.0 | 6624 | 1.7175 | 0.8204 |
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| 0.0077 | 24.0 | 6912 | 1.7680 | 0.8187 |
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| 0.0024 | 25.0 | 7200 | 1.7395 | 0.8206 |
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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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