update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- super_glue
+metrics:
+- accuracy
+model-index:
+- name: yes_no_qna_deberta_model
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: super_glue
+      type: super_glue
+      config: boolq
+      split: train
+      args: boolq
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8507645259938837
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# yes_no_qna_deberta_model
+
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the super_glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5570
+- Accuracy: 0.8508
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.583         | 1.0   | 590  | 0.4086          | 0.8251   |
+| 0.348         | 2.0   | 1180 | 0.4170          | 0.8465   |
+| 0.2183        | 3.0   | 1770 | 0.5570          | 0.8508   |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.0+cu116
+- Datasets 2.8.0
+- Tokenizers 0.13.2