update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- amazon_reviews_multi
+metrics:
+- accuracy
+model-index:
+- name: nli-roberta-base-finetuned-for-amazon-review-ratings
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: amazon_reviews_multi
+      type: amazon_reviews_multi
+      config: en
+      split: validation
+      args: en
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.551
+---
+
+<!-- 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. -->
+
+# nli-roberta-base-finetuned-for-amazon-review-ratings
+
+This model is a fine-tuned version of [cross-encoder/nli-roberta-base](https://huggingface.co/cross-encoder/nli-roberta-base) on the amazon_reviews_multi dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0037
+- Meanabsoluteerror: 0.527
+- Accuracy: 0.551
+
+## 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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Meanabsoluteerror | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:|
+| 0.9999        | 1.0   | 313  | 1.0037          | 0.527             | 0.551    |
+
+
+### Framework versions
+
+- Transformers 4.27.3
+- Pytorch 1.13.1+cu116
+- Datasets 2.10.1
+- Tokenizers 0.13.2