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update model card README.md

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+ ---
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+ license: apache-2.0
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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: token_fine_tunned_flipkart_2
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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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+ # token_fine_tunned_flipkart_2
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3435
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+ - Precision: 0.8797
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+ - Recall: 0.9039
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+ - F1: 0.8916
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+ - Accuracy: 0.9061
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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 | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 109 | 0.5647 | 0.7398 | 0.8123 | 0.7744 | 0.8111 |
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+ | No log | 2.0 | 218 | 0.3863 | 0.8165 | 0.8751 | 0.8448 | 0.8716 |
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+ | No log | 3.0 | 327 | 0.3367 | 0.8599 | 0.8847 | 0.8721 | 0.8869 |
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+ | No log | 4.0 | 436 | 0.3266 | 0.8688 | 0.8911 | 0.8798 | 0.8977 |
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+ | 0.527 | 5.0 | 545 | 0.3508 | 0.8595 | 0.8898 | 0.8744 | 0.8909 |
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+ | 0.527 | 6.0 | 654 | 0.3410 | 0.8748 | 0.9045 | 0.8894 | 0.9009 |
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+ | 0.527 | 7.0 | 763 | 0.3431 | 0.8754 | 0.9045 | 0.8897 | 0.9049 |
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+ | 0.527 | 8.0 | 872 | 0.3435 | 0.8797 | 0.9039 | 0.8916 | 0.9061 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0+cu102
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+ - Datasets 2.2.2
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+ - Tokenizers 0.12.1