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--- |
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library_name: transformers |
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license: mit |
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base_model: xlm-roberta-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: BanglaHealthNER-Model |
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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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# BanglaHealthNER-Model |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2844 |
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- Precision: 0.5616 |
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- Recall: 0.6298 |
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- F1: 0.5937 |
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- Accuracy: 0.8980 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 4 |
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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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| 0.2916 | 1.0 | 1590 | 0.2980 | 0.4946 | 0.5763 | 0.5323 | 0.8890 | |
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| 0.256 | 2.0 | 3180 | 0.2833 | 0.5443 | 0.5831 | 0.5630 | 0.8974 | |
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| 0.2332 | 3.0 | 4770 | 0.2768 | 0.5378 | 0.6292 | 0.5799 | 0.8991 | |
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| 0.1965 | 4.0 | 6360 | 0.2797 | 0.5527 | 0.6208 | 0.5848 | 0.9005 | |
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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 4.1.1 |
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- Tokenizers 0.21.2 |
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