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bert-base-uncased-MLM-scirepeval_fos_chemistry-textCLS-RHEOLOGY
jonas-luehrs/bert-base-uncased-MLM-scirepeval_fos_chemistry-textCLS-RHEOLOGY
bert-base-uncased-MLM-scirepeval_fos_chemistry-textCLS-RHEOLOGY 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023
- SHA
- a8e1ff60
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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-MLM-scirepeval_fos_chemistry-textCLS-RHEOLOGY
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6551
- Accuracy: 0.7516
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 |
|---|---|---|---|---|
| 1.1845 | 1.0 | 46 | 0.9103 | 0.6646 |
| 0.7371 | 2.0 | 92 | 0.7486 | 0.7143 |
| 0.5444 | 3.0 | 138 | 0.6675 | 0.7267 |
| 0.4092 | 4.0 | 184 | 0.6496 | 0.7516 |
| 0.3399 | 5.0 | 230 | 0.6551 | 0.7516 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Aug 16, 2023
- Updated
- Aug 16, 2023