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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - Yaxin/SemEval2016Task5Raw
metrics:
  - accuracy
base_model: bert-large-uncased
model-index:
  - name: bert-large-uncased-semeval2016-laptops
    results:
      - task:
          type: fill-mask
          name: Masked Language Modeling
        dataset:
          name: Yaxin/SemEval2016Task5Raw laptops_english
          type: Yaxin/SemEval2016Task5Raw
          config: laptops_english
          split: validation
          args: laptops_english
        metrics:
          - type: accuracy
            value: 0.7432432432432432
            name: Accuracy

bert-large-uncased-semeval2016-laptops

This model is a fine-tuned version of bert-large-uncased on the Yaxin/SemEval2016Task5Raw laptops_english dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9255
  • Accuracy: 0.7432

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30.0

Training results

Framework versions

  • Transformers 4.29.0.dev0
  • Pytorch 1.13.0
  • Datasets 2.11.0
  • Tokenizers 0.13.2