update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+model-index:
+- name: finetuned-bert-mrpc
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: mrpc
+      split: validation
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8676470588235294
+    - name: F1
+      type: f1
+      value: 0.9065743944636677
+---
+
+<!-- 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. -->
+
+# finetuned-bert-mrpc
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3874
+- Accuracy: 0.8676
+- F1: 0.9066
+
+## 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: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.5751        | 1.0   | 230  | 0.3812          | 0.8284   | 0.8768 |
+| 0.327         | 2.0   | 460  | 0.4207          | 0.8505   | 0.8992 |
+| 0.176         | 3.0   | 690  | 0.3874          | 0.8676   | 0.9066 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.13.3