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xlnet-base-cased_fold_2_binary
elopezlopez/xlnet-base-cased_fold_2_binary
xlnet-base-cased_fold_2_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
- b399df77
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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_2_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: 0.4858
- F1: 0.7648
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 | 290 | 0.4361 | 0.7404 |
| 0.4403 | 2.0 | 580 | 0.5363 | 0.7515 |
| 0.4403 | 3.0 | 870 | 0.4858 | 0.7648 |
| 0.2505 | 4.0 | 1160 | 0.7127 | 0.7612 |
| 0.2505 | 5.0 | 1450 | 0.8930 | 0.7554 |
| 0.1425 | 6.0 | 1740 | 0.9897 | 0.7580 |
| 0.0869 | 7.0 | 2030 | 1.2683 | 0.7615 |
| 0.0869 | 8.0 | 2320 | 1.4988 | 0.7343 |
| 0.0411 | 9.0 | 2610 | 1.5082 | 0.7492 |
| 0.0411 | 10.0 | 2900 | 1.4974 | 0.7450 |
| 0.0306 | 11.0 | 3190 | 1.5723 | 0.7435 |
| 0.0306 | 12.0 | 3480 | 1.8446 | 0.7432 |
| 0.0291 | 13.0 | 3770 | 1.7113 | 0.7639 |
| 0.0207 | 14.0 | 4060 | 1.8073 | 0.7394 |
| 0.0207 | 15.0 | 4350 | 1.7524 | 0.7585 |
| 0.0171 | 16.0 | 4640 | 1.8751 | 0.7374 |
| 0.0171 | 17.0 | 4930 | 1.7849 | 0.7561 |
| 0.0084 | 18.0 | 5220 | 1.8618 | 0.7441 |
| 0.0064 | 19.0 | 5510 | 1.9613 | 0.7437 |
| 0.0064 | 20.0 | 5800 | 1.8898 | 0.7430 |
| 0.006 | 21.0 | 6090 | 1.9889 | 0.7409 |
| 0.006 | 22.0 | 6380 | 1.9949 | 0.7488 |
| 0.0049 | 23.0 | 6670 | 1.9453 | 0.7488 |
| 0.0049 | 24.0 | 6960 | 1.9754 | 0.7472 |
| 0.002 | 25.0 | 7250 | 1.9946 | 0.7504 |
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