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bert-base-uncased-textCLS-RHEOLOGY-20230912
jonas-luehrs/bert-base-uncased-textCLS-RHEOLOGY-20230912
bert-base-uncased-textCLS-RHEOLOGY-20230912 is a text classification model from jonas-luehrs. Use it when you need a label for a piece of text. 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
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Sep 12, 2023
- Updated
- Sep 12, 2023
- SHA
- bc055d2e
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Base models
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-textCLS-RHEOLOGY-20230912
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6383
- Accuracy: 0.7593
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3566 | 1.0 | 46 | 1.1639 | 0.6543 |
| 0.9521 | 2.0 | 92 | 0.8181 | 0.6914 |
| 0.6733 | 3.0 | 138 | 0.6991 | 0.7469 |
| 0.521 | 4.0 | 184 | 0.6459 | 0.7531 |
| 0.444 | 5.0 | 230 | 0.6383 | 0.7593 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 12, 2023
- Updated
- Sep 12, 2023