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DEAT-text
crozierm/DEAT-text
DEAT-text is a text classification model from crozierm. 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
- distilbert
- Access
- Public
- Created
- Apr 8, 2024
- Updated
- Apr 23, 2024
- SHA
- 1faee2d9
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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. -->
DEAT-text
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0486
- Accuracy: 0.9688
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: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.071 | 1.0 | 2500 | 0.0781 | 0.9692 |
| 0.0511 | 2.0 | 5000 | 0.0599 | 0.9679 |
| 0.0521 | 3.0 | 7500 | 0.0502 | 0.9671 |
| 0.0454 | 4.0 | 10000 | 0.0492 | 0.9697 |
| 0.0455 | 5.0 | 12500 | 0.0487 | 0.9684 |
| 0.0447 | 6.0 | 15000 | 0.0486 | 0.9688 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 8, 2024
- Updated
- Apr 23, 2024