update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-uncased-mrpc
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8455882352941176
+    - name: F1
+      type: f1
+      value: 0.8900523560209423
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-mrpc
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6524
+- Accuracy: 0.8456
+- F1: 0.8901
+- Combined Score: 0.8678
+
+## 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: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.06
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| No log        | 1.0   | 230  | 0.4111          | 0.8088   | 0.8704 | 0.8396         |
+| No log        | 2.0   | 460  | 0.3762          | 0.8480   | 0.8942 | 0.8711         |
+| 0.4287        | 3.0   | 690  | 0.5572          | 0.8578   | 0.9024 | 0.8801         |
+| 0.4287        | 4.0   | 920  | 0.6087          | 0.8554   | 0.8977 | 0.8766         |
+| 0.1172        | 5.0   | 1150 | 0.6524          | 0.8456   | 0.8901 | 0.8678         |
+
+
+### Framework versions
+
+- Transformers 4.20.0.dev0
+- Pytorch 1.11.0+cu113
+- Datasets 2.1.0
+- Tokenizers 0.12.1