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xlnet-base-cased_fold_1_binary
elopezlopez/xlnet-base-cased_fold_1_binary
xlnet-base-cased_fold_1_binary is a text classification model from elopezlopez. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlnet
- Access
- Public
- Created
- Jul 31, 2022
- Updated
- Jul 31, 2022
- SHA
- 93cbf833
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
xlnet-base-cased_fold_1_binary
This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7607
- F1: 0.7778
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 288 | 0.4111 | 0.7555 |
| 0.4387 | 2.0 | 576 | 0.4075 | 0.7540 |
| 0.4387 | 3.0 | 864 | 0.5344 | 0.7567 |
| 0.2471 | 4.0 | 1152 | 0.7405 | 0.7597 |
| 0.2471 | 5.0 | 1440 | 1.0564 | 0.7508 |
| 0.1419 | 6.0 | 1728 | 1.0703 | 0.7751 |
| 0.0845 | 7.0 | 2016 | 1.0866 | 0.7609 |
| 0.0845 | 8.0 | 2304 | 1.2135 | 0.7751 |
| 0.05 | 9.0 | 2592 | 1.3649 | 0.7516 |
| 0.05 | 10.0 | 2880 | 1.4943 | 0.7590 |
| 0.0267 | 11.0 | 3168 | 1.5174 | 0.7412 |
| 0.0267 | 12.0 | 3456 | 1.4884 | 0.7559 |
| 0.0278 | 13.0 | 3744 | 1.5109 | 0.7405 |
| 0.0201 | 14.0 | 4032 | 1.7251 | 0.7409 |
| 0.0201 | 15.0 | 4320 | 1.5833 | 0.7354 |
| 0.0185 | 16.0 | 4608 | 1.7744 | 0.7598 |
| 0.0185 | 17.0 | 4896 | 1.8283 | 0.7619 |
| 0.0066 | 18.0 | 5184 | 1.7607 | 0.7778 |
| 0.0066 | 19.0 | 5472 | 1.7503 | 0.7719 |
| 0.0078 | 20.0 | 5760 | 1.7807 | 0.7508 |
| 0.006 | 21.0 | 6048 | 1.6887 | 0.7629 |
| 0.006 | 22.0 | 6336 | 1.7041 | 0.7678 |
| 0.0074 | 23.0 | 6624 | 1.7337 | 0.7633 |
| 0.0074 | 24.0 | 6912 | 1.7548 | 0.7645 |
| 0.0035 | 25.0 | 7200 | 1.7685 | 0.7621 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlnet
- License
- mit
- Created
- Jul 31, 2022
- Updated
- Jul 31, 2022