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bert-base-multilingual-cased-v2
sumeet-hande/bert-base-multilingual-cased-v2
bert-base-multilingual-cased-v2 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
- bert
- Access
- Public
- Created
- Mar 8, 2025
- Updated
- Mar 8, 2025
- SHA
- c0c052e2
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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. -->
bert-base-multilingual-cased-v2
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0127
- Accuracy: 0.7032
- F1: 0.5996
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: 5e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4093 | 1.0 | 81 | 0.3226 | 0.6804 | 0.5810 |
| 0.1271 | 2.0 | 162 | 0.0952 | 0.7170 | 0.6250 |
| 0.029 | 3.0 | 243 | 0.0562 | 0.7226 | 0.6293 |
| 0.0115 | 4.0 | 324 | 0.0429 | 0.7253 | 0.6312 |
| 0.0082 | 5.0 | 405 | 0.0431 | 0.7244 | 0.6303 |
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
- bert
- License
- apache-2.0
- Created
- Mar 8, 2025
- Updated
- Mar 8, 2025