update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- sms_spam
+metrics:
+- accuracy
+model-index:
+- name: roberta-base-finetuned-sms-spam-detection
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: sms_spam
+      type: sms_spam
+      args: plain_text
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.998
+---
+
+<!-- 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. -->
+
+# roberta-base-finetuned-sms-spam-detection
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the sms_spam dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0133
+- Accuracy: 0.998
+
+## 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.0363        | 1.0   | 250  | 0.0156          | 0.996    |
+| 0.0147        | 2.0   | 500  | 0.0133          | 0.998    |
+
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.10.0+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.0