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chembert_cased-MLM-chemistry-tokenCLS-BATTERY
jonas-luehrs/chembert_cased-MLM-chemistry-tokenCLS-BATTERY
chembert_cased-MLM-chemistry-tokenCLS-BATTERY is a token classification model from jonas-luehrs. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 22, 2023
- Updated
- Sep 22, 2023
- SHA
- e65bdbcc
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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-tokenCLS-BATTERY
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: 0.0659
- Precision: 0.6898
- Recall: 0.8528
- F1: 0.7627
- Accuracy: 0.9771
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: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 338 | 0.0783 | 0.6913 | 0.7761 | 0.7312 | 0.9728 |
| 0.1439 | 2.0 | 676 | 0.0633 | 0.6970 | 0.8466 | 0.7645 | 0.9762 |
| 0.0491 | 3.0 | 1014 | 0.0659 | 0.6898 | 0.8528 | 0.7627 | 0.9771 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Sep 22, 2023
- Updated
- Sep 22, 2023