update model card README.md

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-large-cased-finetuned-mrpc
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: GLUE MRPC
+      type: glue
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6838235294117647
+    - name: F1
+      type: f1
+      value: 0.8122270742358079
+---
+
+<!-- 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-large-cased-finetuned-mrpc
+
+This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the GLUE MRPC dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6274
+- Accuracy: 0.6838
+- F1: 0.8122
+- Combined Score: 0.7480
+
+## 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: 4
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6441        | 1.0   | 917  | 0.6370          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6451        | 2.0   | 1834 | 0.6553          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6428        | 3.0   | 2751 | 0.6332          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6476        | 4.0   | 3668 | 0.6248          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6499        | 5.0   | 4585 | 0.6274          | 0.6838   | 0.8122 | 0.7480         |
+
+
+### Framework versions
+
+- Transformers 4.11.0.dev0
+- Pytorch 1.9.0
+- Datasets 1.12.1
+- Tokenizers 0.10.3