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update model card README.md

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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - glue
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: hBERTv1_qnli
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: glue
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+ type: glue
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+ config: qnli
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+ split: validation
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+ args: qnli
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7752150832875709
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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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+ # hBERTv1_qnli
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+
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+ This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1](https://huggingface.co/gokuls/bert_12_layer_model_v1) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7668
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+ - Accuracy: 0.7752
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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: 5e-05
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+ - train_batch_size: 256
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+ - eval_batch_size: 256
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+ - seed: 10
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+ - distributed_type: multi-GPU
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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: 50
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6667 | 1.0 | 410 | 0.5955 | 0.6874 |
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+ | 0.4998 | 2.0 | 820 | 0.4486 | 0.7948 |
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+ | 0.3985 | 3.0 | 1230 | 0.4198 | 0.8113 |
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+ | 0.3106 | 4.0 | 1640 | 0.4841 | 0.7866 |
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+ | 0.2286 | 5.0 | 2050 | 0.5340 | 0.7906 |
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+ | 0.1662 | 6.0 | 2460 | 0.6282 | 0.7728 |
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+ | 0.1237 | 7.0 | 2870 | 0.6678 | 0.7752 |
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+ | 0.0945 | 8.0 | 3280 | 0.7668 | 0.7752 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Pytorch 1.14.0a0+410ce96
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2