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bert-large-cased-sigir-LR100-1-cased-40
jojoUla/bert-large-cased-sigir-LR100-1-cased-40
bert-large-cased-sigir-LR100-1-cased-40 is a fill-mask model from jojoUla. 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
- Feb 4, 2023
- Updated
- Feb 4, 2023
- SHA
- 97a6539a
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-cased-sigir-LR100-1-cased-40
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2085
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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.661 | 1.0 | 1 | 6.7088 |
| 7.1425 | 2.0 | 2 | 7.0634 |
| 6.8918 | 3.0 | 3 | 6.2872 |
| 6.1875 | 4.0 | 4 | 5.5826 |
| 5.6201 | 5.0 | 5 | 5.4365 |
| 5.181 | 6.0 | 6 | 3.7720 |
| 5.0548 | 7.0 | 7 | 5.5019 |
| 4.3957 | 8.0 | 8 | 3.2004 |
| 3.993 | 9.0 | 9 | 2.4284 |
| 3.593 | 10.0 | 10 | 3.2126 |
| 3.754 | 11.0 | 11 | 2.7146 |
| 3.061 | 12.0 | 12 | 2.5308 |
| 3.0496 | 13.0 | 13 | 2.8430 |
| 3.1128 | 14.0 | 14 | 1.2934 |
| 2.7098 | 15.0 | 15 | 1.5709 |
| 2.5303 | 16.0 | 16 | 1.9032 |
| 2.3475 | 17.0 | 17 | 2.1788 |
| 2.4054 | 18.0 | 18 | 1.5836 |
| 2.6168 | 19.0 | 19 | 3.7077 |
| 2.5972 | 20.0 | 20 | 2.8996 |
| 2.287 | 21.0 | 21 | 2.1028 |
| 2.1383 | 22.0 | 22 | 2.0755 |
| 2.443 | 23.0 | 23 | 1.6498 |
| 2.0233 | 24.0 | 24 | 2.2023 |
| 2.2446 | 25.0 | 25 | 2.4627 |
| 1.9087 | 26.0 | 26 | 2.3244 |
| 2.1685 | 27.0 | 27 | 1.9509 |
| 1.9055 | 28.0 | 28 | 2.6149 |
| 1.9063 | 29.0 | 29 | 2.0499 |
| 2.3587 | 30.0 | 30 | 1.1757 |
| 2.0389 | 31.0 | 31 | 1.1181 |
| 1.9223 | 32.0 | 32 | 1.6205 |
| 2.0361 | 33.0 | 33 | 1.8381 |
| 2.1823 | 34.0 | 34 | 0.7964 |
| 2.2411 | 35.0 | 35 | 2.0179 |
| 1.8976 | 36.0 | 36 | 1.1467 |
| 1.9321 | 37.0 | 37 | 1.5334 |
| 2.257 | 38.0 | 38 | 2.1575 |
| 2.0543 | 39.0 | 39 | 1.5084 |
| 1.7383 | 40.0 | 40 | 1.8176 |
Framework versions
- Transformers 4.26.0
- 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
- Feb 4, 2023
- Updated
- Feb 4, 2023