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mayo-bert-event-uncased-wordlevel-block512-batch8-ep10
hsohn3/mayo-bert-event-uncased-wordlevel-block512-batch8-ep10
mayo-bert-event-uncased-wordlevel-block512-batch8-ep10 is a fill-mask model from hsohn3. 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
- Jul 5, 2022
- Updated
- Jul 5, 2022
- SHA
- b7d6786f
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. -->
hsohn3/mayo-bert-event-uncased-wordlevel-block512-batch8-ep10
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: 3.3986
- Epoch: 9
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 | Epoch |
|---|---|
| 4.4687 | 0 |
| 3.5471 | 1 |
| 3.4820 | 2 |
| 3.4552 | 3 |
| 3.4350 | 4 |
| 3.4223 | 5 |
| 3.4073 | 6 |
| 3.4086 | 7 |
| 3.3995 | 8 |
| 3.3986 | 9 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 5, 2022
- Updated
- Jul 5, 2022