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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_7_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_7_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: 1.7774
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- F1: 0.8111
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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 | 0.4189 | 0.7903 |
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| 0.432 | 2.0 | 576 | 0.3927 | 0.8045 |
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| 0.432 | 3.0 | 864 | 0.4868 | 0.8108 |
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| 0.2573 | 4.0 | 1152 | 0.6763 | 0.8019 |
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| 0.2573 | 5.0 | 1440 | 0.8132 | 0.8105 |
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| 0.1612 | 6.0 | 1728 | 0.8544 | 0.8086 |
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| 0.0972 | 7.0 | 2016 | 1.1274 | 0.8109 |
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| 0.0972 | 8.0 | 2304 | 1.2622 | 0.8056 |
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| 0.0515 | 9.0 | 2592 | 1.3398 | 0.8013 |
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| 0.0515 | 10.0 | 2880 | 1.5421 | 0.8082 |
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| 0.0244 | 11.0 | 3168 | 1.4931 | 0.8042 |
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| 0.0244 | 12.0 | 3456 | 1.5744 | 0.8045 |
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| 0.0287 | 13.0 | 3744 | 1.4169 | 0.8091 |
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| 0.0255 | 14.0 | 4032 | 1.5790 | 0.7999 |
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| 0.0255 | 15.0 | 4320 | 1.6094 | 0.7994 |
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| 0.0098 | 16.0 | 4608 | 1.5758 | 0.8006 |
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| 0.0098 | 17.0 | 4896 | 1.5326 | 0.8140 |
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| 0.0203 | 18.0 | 5184 | 1.6431 | 0.8114 |
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| 0.0203 | 19.0 | 5472 | 1.7105 | 0.8072 |
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| 0.0104 | 20.0 | 5760 | 1.6353 | 0.8139 |
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| 0.0062 | 21.0 | 6048 | 1.6762 | 0.8108 |
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| 0.0062 | 22.0 | 6336 | 1.7076 | 0.8106 |
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| 0.0088 | 23.0 | 6624 | 1.7887 | 0.8035 |
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| 0.0088 | 24.0 | 6912 | 1.7731 | 0.8099 |
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| 0.0026 | 25.0 | 7200 | 1.7774 | 0.8111 |
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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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