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sentence-classifiert
Meli101/sentence-classifiert
sentence-classifiert is a text classification model from Meli101. 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
- Feb 19, 2024
- Updated
- Feb 19, 2024
- SHA
- 510b4718
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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. -->
sentence-classifiert
This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3410
- Precision: 0.9085
- Recall: 0.9068
- Accuracy: 0.9072
- F1: 0.9072
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 | Precision | Recall | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 154 | 0.4158 | 0.8549 | 0.8445 | 0.8438 | 0.8443 |
| No log | 2.0 | 308 | 0.3426 | 0.8875 | 0.8804 | 0.8796 | 0.8787 |
| No log | 3.0 | 462 | 0.3594 | 0.8945 | 0.8856 | 0.8869 | 0.8868 |
| 0.3638 | 4.0 | 616 | 0.3302 | 0.9034 | 0.9008 | 0.9015 | 0.9014 |
| 0.3638 | 5.0 | 770 | 0.3410 | 0.9085 | 0.9068 | 0.9072 | 0.9072 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Feb 19, 2024
- Updated
- Feb 19, 2024