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bert-large-uncased-finetuned-bert-large-uncase-p3
jbdaniel/bert-large-uncased-finetuned-bert-large-uncase-p3
bert-large-uncased-finetuned-bert-large-uncase-p3 is a fill-mask model from jbdaniel. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Dec 27, 2022
- Updated
- Feb 15, 2023
- SHA
- 01c779ca
Try a prompt
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. -->
bert-large-uncased-finetuned-bert-large-uncase-p3
This model is a fine-tuned version of bert-large-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6764
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.798 | 1.0 | 5696 | 1.7244 |
| 1.6767 | 2.0 | 11392 | 1.6983 |
| 1.6421 | 3.0 | 17088 | 1.6764 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 27, 2022
- Updated
- Feb 15, 2023