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distilbert-foundation-category-c5-finetune
eric-mc2/distilbert-foundation-category-c5-finetune
distilbert-foundation-category-c5-finetune is a text classification model from eric-mc2. 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
- Jan 10, 2024
- Updated
- Jan 10, 2024
- SHA
- bcbbbb40
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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. -->
distilbert-foundation-category-c5-finetune
This model is a fine-tuned version of thedavidhackett/distilbert-foundation-category-c5 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2711
- Accuracy: 0.9375
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.275 | 1.0 | 225 | 0.1805 | 0.9425 |
| 0.182 | 2.0 | 450 | 0.2120 | 0.94 |
| 0.135 | 3.0 | 675 | 0.2513 | 0.9325 |
| 0.0989 | 4.0 | 900 | 0.2707 | 0.9375 |
| 0.0862 | 5.0 | 1125 | 0.2711 | 0.9375 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jan 10, 2024
- Updated
- Jan 10, 2024