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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - np
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+ base_model: RoBERTa
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: RoBERTa-devangari-script-classification
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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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+ # RoBERTa-devangari-script-classification
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+
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+ This model is a fine-tuned version of [RoBERTa](https://huggingface.co/RoBERTa) on the Custom Devangari Datasets dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0329
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+ - Accuracy: 0.9935
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+ - F1: 0.9935
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+ - Precision: 0.9935
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+ - Recall: 0.9935
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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: 3e-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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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: 500
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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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 | Precision | Recall |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.2337 | 0.9997 | 1638 | 0.0603 | 0.9874 | 0.9874 | 0.9875 | 0.9874 |
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+ | 0.0513 | 2.0 | 3277 | 0.0387 | 0.9919 | 0.9919 | 0.9919 | 0.9919 |
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+ | 0.0252 | 2.9991 | 4914 | 0.0329 | 0.9935 | 0.9935 | 0.9935 | 0.9935 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.19.1
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