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bert-base-uncased-finetuned-QnA
mujerry/bert-base-uncased-finetuned-QnA
bert-base-uncased-finetuned-QnA is a fill-mask model from mujerry. 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
- Mar 2, 2022
- Updated
- Jul 27, 2021
- SHA
- 4680faa1
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-base-uncased-finetuned-QnA
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0604
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 |
|---|---|---|---|
| No log | 1.0 | 20 | 3.4894 |
| No log | 2.0 | 40 | 3.5654 |
| No log | 3.0 | 60 | 3.3185 |
| No log | 4.0 | 80 | 3.2859 |
| No log | 5.0 | 100 | 3.2947 |
| No log | 6.0 | 120 | 3.3998 |
| No log | 7.0 | 140 | 3.1642 |
| No log | 8.0 | 160 | 3.2653 |
| No log | 9.0 | 180 | 3.3427 |
| No log | 10.0 | 200 | 3.3549 |
Framework versions
- Transformers 4.9.1
- Pytorch 1.9.0+cu102
- Datasets 1.10.2
- Tokenizers 0.10.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Jul 27, 2021