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nepali_complaints_classification_nepbert3

Text Classification
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bert
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README.md ADDED
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+ ---
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+ base_model: Rajan/NepaliBERT
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: nepali_complaints_classification_nepbert3
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+ results: []
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+ ---
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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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+
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+ # nepali_complaints_classification_nepbert3
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+
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+ This model is a fine-tuned version of [Rajan/NepaliBERT](https://huggingface.co/Rajan/NepaliBERT) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2687
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+ - Accuracy: 0.9494
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+ - F1-score: 0.9483
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
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+ | 1.4921 | 0.22 | 500 | 0.8642 | 0.7235 | 0.7143 |
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+ | 0.7781 | 0.45 | 1000 | 0.6241 | 0.7974 | 0.7923 |
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+ | 0.5865 | 0.67 | 1500 | 0.5342 | 0.8243 | 0.8125 |
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+ | 0.4625 | 0.89 | 2000 | 0.4250 | 0.8576 | 0.8553 |
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+ | 0.3648 | 1.11 | 2500 | 0.3856 | 0.8759 | 0.8725 |
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+ | 0.3001 | 1.34 | 3000 | 0.3424 | 0.8899 | 0.8891 |
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+ | 0.2723 | 1.56 | 3500 | 0.3199 | 0.9007 | 0.8981 |
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+ | 0.2538 | 1.78 | 4000 | 0.2898 | 0.9085 | 0.9066 |
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+ | 0.231 | 2.01 | 4500 | 0.2676 | 0.9203 | 0.9189 |
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+ | 0.1478 | 2.23 | 5000 | 0.3029 | 0.9210 | 0.9187 |
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+ | 0.1666 | 2.45 | 5500 | 0.2580 | 0.9283 | 0.9271 |
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+ | 0.1519 | 2.67 | 6000 | 0.2573 | 0.9308 | 0.9292 |
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+ | 0.1498 | 2.9 | 6500 | 0.2746 | 0.9328 | 0.9306 |
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+ | 0.1112 | 3.12 | 7000 | 0.2564 | 0.9398 | 0.9389 |
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+ | 0.0903 | 3.34 | 7500 | 0.2726 | 0.9403 | 0.9393 |
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+ | 0.1036 | 3.57 | 8000 | 0.2664 | 0.9398 | 0.9385 |
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+ | 0.1043 | 3.79 | 8500 | 0.2614 | 0.9459 | 0.9447 |
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+ | 0.0972 | 4.01 | 9000 | 0.2499 | 0.9453 | 0.9443 |
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+ | 0.0663 | 4.23 | 9500 | 0.2643 | 0.9469 | 0.9458 |
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+ | 0.0683 | 4.46 | 10000 | 0.2688 | 0.9474 | 0.9462 |
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+ | 0.0671 | 4.68 | 10500 | 0.2657 | 0.9491 | 0.9481 |
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+ | 0.0605 | 4.9 | 11000 | 0.2687 | 0.9494 | 0.9483 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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