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finetuning-sentiment-model-roberta

This model was trained from scratch on the imdb dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2171
  • Accuracy: 0.93
  • F1: 0.9298
  • Precision: 0.9329
  • Recall: 0.9267

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
0.144 0.98 46 0.2348 0.91 0.9132 0.8820 0.9467
0.0957 1.98 93 0.2171 0.93 0.9298 0.9329 0.9267
0.08 2.94 138 0.2554 0.9133 0.9167 0.8827 0.9533

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train zijuncheng/finetuning-sentiment-model-roberta

Evaluation results