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xlnet-base-rte-finetuned
vish88/xlnet-base-rte-finetuned
xlnet-base-rte-finetuned is a text classification model from vish88. 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 24, 2022
- Updated
- Jul 25, 2022
- SHA
- d8bfe91c
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Datasets
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-rte-finetuned
This model is a fine-tuned version of xlnet-base-cased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 2.6688
- Accuracy: 0.7040
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 311 | 0.9695 | 0.6859 |
| 0.315 | 2.0 | 622 | 2.2516 | 0.6498 |
| 0.315 | 3.0 | 933 | 2.0439 | 0.7076 |
| 0.1096 | 4.0 | 1244 | 2.5190 | 0.7040 |
| 0.0368 | 5.0 | 1555 | 2.6688 | 0.7040 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlnet
- License
- mit
- Created
- Jul 24, 2022
- Updated
- Jul 25, 2022