update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- rotten_tomatoes_movie_review
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert-base-cased-finetuned-rotten-tomatoes-epochs-5
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: rotten_tomatoes_movie_review
+      type: rotten_tomatoes_movie_review
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.975609756097561
+    - name: F1
+      type: f1
+      value: 0.9756096702430234
+---
+
+<!-- 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-cased-finetuned-rotten-tomatoes-epochs-5
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the rotten_tomatoes_movie_review dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1022
+- Accuracy: 0.9756
+- F1: 0.9756
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.595         | 1.0   | 34   | 0.3926          | 0.8780   | 0.8780 |
+| 0.3767        | 2.0   | 68   | 0.2374          | 0.9390   | 0.9390 |
+| 0.273         | 3.0   | 102  | 0.1522          | 0.9615   | 0.9615 |
+| 0.1597        | 4.0   | 136  | 0.1154          | 0.9719   | 0.9719 |
+| 0.1348        | 5.0   | 170  | 0.1022          | 0.9756   | 0.9756 |
+
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 2.1.0+cu121
+- Datasets 1.16.1
+- Tokenizers 0.15.0