update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: benchmark-finetuned-bert
+  results: []
+---
+
+<!-- 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. -->
+
+# benchmark-finetuned-bert
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4553
+- Accuracy: 0.8267
+- F1: 0.8270
+
+## 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: 64
+- eval_batch_size: 64
+- 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 | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.803         | 1.0   | 48   | 0.6463          | 0.6997   | 0.6460 |
+| 0.5508        | 2.0   | 96   | 0.5141          | 0.8042   | 0.8051 |
+| 0.4111        | 3.0   | 144  | 0.4553          | 0.8267   | 0.8270 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1