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bert-base-uncased-finetuned-ED_BERT_test
Mohammed245/bert-base-uncased-finetuned-ED_BERT_test
bert-base-uncased-finetuned-ED_BERT_test is a fill-mask model from Mohammed245. 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.
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
- May 18, 2022
- Updated
- May 27, 2022
- SHA
- a8ba9daa
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
Mohammed245/bert-base-uncased-finetuned-ED_BERT_test
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 4.9663
- Validation Loss: 5.2474
- Epoch: 1
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 6.2084 | 5.6239 | 0 |
| 4.9663 | 5.2474 | 1 |
Framework versions
- Transformers 4.18.0
- TensorFlow 2.4.0
- Datasets 2.2.1
- Tokenizers 0.11.0
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 18, 2022
- Updated
- May 27, 2022