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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_2_binary
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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_2_binary
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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: 0.4858
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- F1: 0.7648
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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 | 0.4361 | 0.7404 |
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| 0.4403 | 2.0 | 580 | 0.5363 | 0.7515 |
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| 0.4403 | 3.0 | 870 | 0.4858 | 0.7648 |
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| 0.2505 | 4.0 | 1160 | 0.7127 | 0.7612 |
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| 0.2505 | 5.0 | 1450 | 0.8930 | 0.7554 |
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| 0.1425 | 6.0 | 1740 | 0.9897 | 0.7580 |
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| 0.0869 | 7.0 | 2030 | 1.2683 | 0.7615 |
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| 0.0869 | 8.0 | 2320 | 1.4988 | 0.7343 |
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| 0.0411 | 9.0 | 2610 | 1.5082 | 0.7492 |
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| 0.0411 | 10.0 | 2900 | 1.4974 | 0.7450 |
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| 0.0306 | 11.0 | 3190 | 1.5723 | 0.7435 |
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| 0.0306 | 12.0 | 3480 | 1.8446 | 0.7432 |
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| 0.0291 | 13.0 | 3770 | 1.7113 | 0.7639 |
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| 0.0207 | 14.0 | 4060 | 1.8073 | 0.7394 |
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| 0.0207 | 15.0 | 4350 | 1.7524 | 0.7585 |
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| 0.0171 | 16.0 | 4640 | 1.8751 | 0.7374 |
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| 0.0171 | 17.0 | 4930 | 1.7849 | 0.7561 |
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| 0.0084 | 18.0 | 5220 | 1.8618 | 0.7441 |
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| 0.0064 | 19.0 | 5510 | 1.9613 | 0.7437 |
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| 0.0064 | 20.0 | 5800 | 1.8898 | 0.7430 |
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| 0.006 | 21.0 | 6090 | 1.9889 | 0.7409 |
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| 0.006 | 22.0 | 6380 | 1.9949 | 0.7488 |
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| 0.0049 | 23.0 | 6670 | 1.9453 | 0.7488 |
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| 0.0049 | 24.0 | 6960 | 1.9754 | 0.7472 |
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| 0.002 | 25.0 | 7250 | 1.9946 | 0.7504 |
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### Framework versions
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- Transformers 4.21.0
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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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