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aesthetic_attribute_classifier

This model is a fine-tuned version of distilbert-base-uncased on the PCCD dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3976
  • Precision: {'precision': 0.877129341279301}
  • Recall: {'recall': 0.8751381215469614}
  • F1: {'f1': 0.875529982855803}
  • Accuracy: {'accuracy': 0.8751381215469614}

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: 5

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.452 1.0 1528 0.4109 {'precision': 0.8632779077963935} {'recall': 0.8615101289134438} {'f1': 0.8618616182904953} {'accuracy': 0.8615101289134438}
0.3099 2.0 3056 0.3976 {'precision': 0.877129341279301} {'recall': 0.8751381215469614} {'f1': 0.875529982855803} {'accuracy': 0.8751381215469614}
0.227 3.0 4584 0.4320 {'precision': 0.876211408446225} {'recall': 0.874401473296501} {'f1': 0.8747427955387239} {'accuracy': 0.874401473296501}
0.1645 4.0 6112 0.4840 {'precision': 0.8724641667216837} {'recall': 0.8714548802946593} {'f1': 0.8714577820909117} {'accuracy': 0.8714548802946593}
0.1141 5.0 7640 0.5083 {'precision': 0.8755445355051571} {'recall': 0.8747697974217311} {'f1': 0.8748766125899489} {'accuracy': 0.8747697974217311}

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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