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distilbert-base-multilingual-cased-v3
sumeet-hande/distilbert-base-multilingual-cased-v3
distilbert-base-multilingual-cased-v3 is a token classification model from sumeet-hande. Use it when you need labels on individual words, such as names. 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
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 1, 2025
- Updated
- Mar 1, 2025
- SHA
- 129d557d
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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-v3
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0799
- Accuracy: 0.7610
- F1: 0.6806
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: 7e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.5768 | 1.0 | 58 | 0.3674 | 0.6489 | 0.5492 |
| 0.1531 | 2.0 | 116 | 0.0976 | 0.6982 | 0.6041 |
| 0.0511 | 3.0 | 174 | 0.0493 | 0.7048 | 0.6114 |
| 0.0331 | 4.0 | 232 | 0.0301 | 0.7081 | 0.6153 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 1, 2025
- Updated
- Mar 1, 2025