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distilbert-foundation-category-c6-finetune
thedavidhackett/distilbert-foundation-category-c6-finetune
distilbert-foundation-category-c6-finetune is a text classification model from thedavidhackett. 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 9, 2024
- Updated
- Jan 9, 2024
- SHA
- b159127e
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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-c6-finetune
This model is a fine-tuned version of eric-mc2/distilbert-foundation-category-c6 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1598
- Accuracy: 0.955
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 |
|---|---|---|---|---|
| 0.2225 | 1.0 | 225 | 0.1531 | 0.9575 |
| 0.1476 | 2.0 | 450 | 0.1731 | 0.9575 |
| 0.1025 | 3.0 | 675 | 0.1502 | 0.955 |
| 0.0796 | 4.0 | 900 | 0.1465 | 0.955 |
| 0.0627 | 5.0 | 1125 | 0.1598 | 0.955 |
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 9, 2024
- Updated
- Jan 9, 2024