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roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-270000sample
HPL/roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-270000sample
roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-270000sample is a fill-mask model from HPL. 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
- Jan 5, 2023
- Updated
- Jan 5, 2023
- SHA
- 9f7c44ba
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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-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-270000sample
This model is a fine-tuned version of HPL/roberta-large-unlabeled-labeled-gab-reddit-task-semeval2023-t10-210000sample on the None dataset.
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Framework versions
- Transformers 4.13.0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.10.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Jan 5, 2023
- Updated
- Jan 5, 2023