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update model card README.md

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+ ---
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+ license: mit
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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: roberta-base-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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+ args: qnli
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9229361156873512
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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-base-qnli
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4277
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+ - Accuracy: 0.9229
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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: 8
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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_ratio: 0.06
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+ - num_epochs: 10.0
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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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+ | 0.2986 | 1.0 | 6547 | 0.2215 | 0.9171 |
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+ | 0.243 | 2.0 | 13094 | 0.2321 | 0.9173 |
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+ | 0.2048 | 3.0 | 19641 | 0.2992 | 0.9246 |
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+ | 0.1629 | 4.0 | 26188 | 0.3538 | 0.9220 |
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+ | 0.1308 | 5.0 | 32735 | 0.3533 | 0.9209 |
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+ | 0.0846 | 6.0 | 39282 | 0.4277 | 0.9229 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.20.0.dev0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1