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finetuned_token_2e-05_16_02_2022-14_15_41

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1746
  • Precision: 0.3191
  • Recall: 0.3382
  • F1: 0.3284
  • Accuracy: 0.9439

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: 32
  • eval_batch_size: 32
  • 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
No log 1.0 38 0.2908 0.1104 0.1905 0.1398 0.8731
No log 2.0 76 0.2253 0.1682 0.3206 0.2206 0.9114
No log 3.0 114 0.2041 0.2069 0.3444 0.2585 0.9249
No log 4.0 152 0.1974 0.2417 0.3603 0.2894 0.9269
No log 5.0 190 0.1958 0.2707 0.3683 0.3120 0.9299

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.1+cu113
  • Datasets 1.18.0
  • Tokenizers 0.10.3
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