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chembert_cased-MLM-chemistry-textCLS-PETROCHEMICAL
jonas-luehrs/chembert_cased-MLM-chemistry-textCLS-PETROCHEMICAL
chembert_cased-MLM-chemistry-textCLS-PETROCHEMICAL 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
- Sep 22, 2023
- Updated
- Sep 22, 2023
- SHA
- dad0a654
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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. -->
chembert_cased-MLM-chemistry-textCLS-PETROCHEMICAL
This model is a fine-tuned version of jonas-luehrs/chembert_cased-MLM-chemistry on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5883
- F1: 0.7662
- Precision: 0.7616
- Recall: 0.7838
- Accuracy: 0.7838
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.1285 | 1.0 | 125 | 0.7318 | 0.7165 | 0.7123 | 0.7297 | 0.7297 |
| 0.6049 | 2.0 | 250 | 0.6196 | 0.7524 | 0.7483 | 0.7703 | 0.7703 |
| 0.4449 | 3.0 | 375 | 0.5883 | 0.7662 | 0.7616 | 0.7838 | 0.7838 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 22, 2023
- Updated
- Sep 22, 2023