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dbert-categ-classification
pppereira3/dbert-categ-classification
dbert-categ-classification is a text classification model from pppereira3. 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
- Oct 30, 2024
- Updated
- Oct 30, 2024
- SHA
- d86e978c
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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. -->
dbert-categ-classification
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: 1.4167
- Accuracy: 0.59
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 438 | 1.1975 | 0.5773 |
| 1.4332 | 2.0 | 876 | 1.1615 | 0.597 |
| 0.9406 | 3.0 | 1314 | 1.1965 | 0.591 |
| 0.6737 | 4.0 | 1752 | 1.3056 | 0.591 |
| 0.4963 | 5.0 | 2190 | 1.4167 | 0.59 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 30, 2024
- Updated
- Oct 30, 2024