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--- |
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library_name: transformers |
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license: mit |
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base_model: sagorsarker/bangla-bert-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: bangla-bert-base-finetuned-ner-generated_data |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bangla-bert-base-finetuned-ner-generated_data |
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This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4845 |
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- Precision: 0.7016 |
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- Recall: 0.6578 |
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- F1: 0.6790 |
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- Accuracy: 0.8859 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 50 |
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- eval_batch_size: 50 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 353 | 0.4879 | 0.6705 | 0.5821 | 0.6232 | 0.8735 | |
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| 0.4957 | 2.0 | 706 | 0.4439 | 0.7046 | 0.6172 | 0.6580 | 0.8855 | |
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| 0.3208 | 3.0 | 1059 | 0.4374 | 0.6977 | 0.6563 | 0.6764 | 0.8895 | |
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| 0.3208 | 4.0 | 1412 | 0.4482 | 0.7183 | 0.6470 | 0.6808 | 0.8933 | |
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| 0.2344 | 5.0 | 1765 | 0.4610 | 0.6920 | 0.6715 | 0.6816 | 0.8908 | |
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| 0.1868 | 6.0 | 2118 | 0.4703 | 0.6987 | 0.6680 | 0.6830 | 0.8917 | |
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### Framework versions |
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- Transformers 4.53.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
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