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MuRIL_for_TeluguQC

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/muril-base-cased
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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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+ - accuracy
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+ model-index:
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+ - name: Muril-base-finetune-Telugu-qc
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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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+ # Muril-base-finetune-Telugu-qc
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+
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+ This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6250
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+ - Precision: 0.7716
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+ - Recall: 0.7647
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+ - Accuracy: 0.7647
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+ - F1-score: 0.7587
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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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+ - num_epochs: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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+ | 1.7858 | 1.0 | 32 | 1.7821 | 0.0454 | 0.2130 | 0.2130 | 0.0748 |
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+ | 1.7526 | 2.0 | 64 | 1.7539 | 0.1754 | 0.2860 | 0.2860 | 0.1866 |
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+ | 1.7112 | 3.0 | 96 | 1.7232 | 0.3352 | 0.3043 | 0.3043 | 0.2168 |
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+ | 1.6655 | 4.0 | 128 | 1.6832 | 0.7122 | 0.6166 | 0.6166 | 0.6194 |
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+ | 1.6217 | 5.0 | 160 | 1.6496 | 0.7708 | 0.7688 | 0.7688 | 0.7629 |
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+ | 1.5898 | 6.0 | 192 | 1.6431 | 0.7618 | 0.7424 | 0.7424 | 0.7379 |
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+ | 1.5678 | 7.0 | 224 | 1.6285 | 0.7697 | 0.7627 | 0.7627 | 0.7565 |
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+ | 1.5572 | 8.0 | 256 | 1.6250 | 0.7716 | 0.7647 | 0.7647 | 0.7587 |
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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 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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+ "BertForSequenceClassification"
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+ "4": "Location",
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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