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IQA_classification

This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0718
  • Accuracy: 0.4862
  • Precision: 0.3398
  • Recall: 0.4862
  • F1: 0.3270

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 Precision Recall F1
1.3973 1.0 28 1.1588 0.4771 0.2276 0.4771 0.3082
1.1575 2.0 56 1.0718 0.4862 0.3398 0.4862 0.3270

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0+cu113
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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Evaluation results