Halim A
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metadata
license: apache-2.0
base_model: cross-encoder/nli-roberta-base
tags:
  - generated_from_trainer
datasets:
  - amazon_reviews_multi
metrics:
  - accuracy
model-index:
  - name: nli-roberta-base-finetuned-for-amazon-review-ratings2
    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: 0.55

nli-roberta-base-finetuned-for-amazon-review-ratings2

This model is a fine-tuned version of cross-encoder/nli-roberta-base on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0153
  • Meanabsoluteerror: 0.538
  • Accuracy: 0.55

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
1.1358 1.0 313 1.0153 0.538 0.55

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3