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distilbert-base-multilingual-cased-aoe-en-indo
cvapict/distilbert-base-multilingual-cased-aoe-en-indo
distilbert-base-multilingual-cased-aoe-en-indo 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 21, 2024
- Updated
- Nov 21, 2024
- SHA
- b70084e9
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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-en-indo
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: 0.3997
- Accuracy: 0.8715
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: 32
- eval_batch_size: 8
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2904 | 1.0 | 292 | 0.3097 | 0.8698 |
| 0.3509 | 2.0 | 584 | 0.2919 | 0.8745 |
| 0.2116 | 3.0 | 876 | 0.3302 | 0.8728 |
| 0.225 | 4.0 | 1168 | 0.3540 | 0.8702 |
| 0.1239 | 5.0 | 1460 | 0.3997 | 0.8715 |
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 21, 2024
- Updated
- Nov 21, 2024