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roberta-base-unlabeled-TAPT-1
simonkHug/roberta-base-unlabeled-TAPT-1
roberta-base-unlabeled-TAPT-1 is a fill-mask model from simonkHug. Use it when you need the model to fill a missing word. 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
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Apr 24, 2023
- Updated
- Apr 24, 2023
- SHA
- 88b328f0
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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. -->
roberta-base-unlabeled-TAPT-1
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.8919
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.427 | 1.0 | 310 | 7.1961 |
| 6.8282 | 2.0 | 620 | 7.0971 |
| 6.8506 | 3.0 | 930 | 7.0804 |
| 6.8025 | 4.0 | 1240 | 7.0368 |
| 6.7381 | 5.0 | 1550 | 7.0475 |
| 6.7148 | 6.0 | 1860 | 7.0130 |
| 6.688 | 7.0 | 2170 | 6.9824 |
| 6.6814 | 8.0 | 2480 | 6.9456 |
| 6.7029 | 9.0 | 2790 | 7.0011 |
| 6.6686 | 10.0 | 3100 | 7.0099 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Apr 24, 2023
- Updated
- Apr 24, 2023