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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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+ - f1
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+ model-index:
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+ - name: deberta-large-finetuned-mrpc
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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: mrpc
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+ split: validation
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+ args: mrpc
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9044117647058824
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+ - name: F1
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+ type: f1
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+ value: 0.9307282415630549
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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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+ # deberta-large-finetuned-mrpc
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+
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+ This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on the glue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5845
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+ - Accuracy: 0.9044
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+ - F1: 0.9307
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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: 87
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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: 5
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 230 | 0.3173 | 0.8848 | 0.9180 |
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+ | No log | 2.0 | 460 | 0.3501 | 0.8799 | 0.9127 |
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+ | 0.3071 | 3.0 | 690 | 0.5214 | 0.8946 | 0.9239 |
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+ | 0.3071 | 4.0 | 920 | 0.5542 | 0.9118 | 0.9366 |
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+ | 0.0619 | 5.0 | 1150 | 0.5845 | 0.9044 | 0.9307 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.13.3