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distilbert-base-multilingual-cased-aoe-test11-ratio1to2
cvapict/distilbert-base-multilingual-cased-aoe-test11-ratio1to2
distilbert-base-multilingual-cased-aoe-test11-ratio1to2 is a text classification model from cvapict. 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
- Nov 27, 2024
- Updated
- Nov 27, 2024
- SHA
- ffa0fccc
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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-base-multilingual-cased-aoe-test11-ratio1to2
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3188
- Accuracy: 0.8670
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3817 | 1.0 | 55 | 0.3402 | 0.8477 |
| 0.3213 | 2.0 | 110 | 0.3575 | 0.8534 |
| 0.2823 | 3.0 | 165 | 0.3188 | 0.8670 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 27, 2024
- Updated
- Nov 27, 2024