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bengali_pos_v1_500000
mHossain/bengali_pos_v1_500000
bengali_pos_v1_500000 is a token classification model from mHossain. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- electra
- Access
- Public
- Created
- Jan 1, 2024
- Updated
- Jan 1, 2024
- SHA
- 8791cf1a
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Base models
Datasets
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. -->
bengali_pos_v1_500000
This model is a fine-tuned version of mHossain/bengali_pos_v1_400000 on the pos_tag_100k dataset. It achieves the following results on the evaluation set:
- Loss: 0.6185
- Precision: 0.7517
- Recall: 0.7533
- F1: 0.7525
- Accuracy: 0.8149
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6508 | 1.0 | 67500 | 0.6325 | 0.7386 | 0.7396 | 0.7391 | 0.8041 |
| 0.5713 | 2.0 | 135000 | 0.6093 | 0.7487 | 0.7500 | 0.7493 | 0.8123 |
| 0.4789 | 3.0 | 202500 | 0.6185 | 0.7517 | 0.7533 | 0.7525 | 0.8149 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- electra
- Created
- Jan 1, 2024
- Updated
- Jan 1, 2024