hindi-distilbert-ner
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: 0.0287
- Precision: 0.8882
- Recall: 0.9279
- F1: 0.9076
- Accuracy: 0.9934
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: 1e-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 |
---|---|---|---|---|---|---|---|
0.3007 | 1.0 | 882 | 0.0731 | 0.7217 | 0.7906 | 0.7546 | 0.9807 |
0.0541 | 2.0 | 1764 | 0.0392 | 0.8475 | 0.9088 | 0.8771 | 0.9905 |
0.0274 | 3.0 | 2646 | 0.0287 | 0.8882 | 0.9279 | 0.9076 | 0.9934 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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