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run-3

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

  • Loss: 2.4223
  • Accuracy: 0.75
  • Precision: 0.7128
  • Recall: 0.6998
  • F1: 0.7043

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: 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
1.0025 1.0 50 0.8925 0.63 0.6703 0.5704 0.5060
0.8187 2.0 100 0.7915 0.595 0.6007 0.5926 0.5344
0.5671 3.0 150 0.9573 0.695 0.6520 0.6350 0.6380
0.3218 4.0 200 0.9195 0.68 0.6447 0.6539 0.6461
0.2208 5.0 250 1.2429 0.715 0.6801 0.6617 0.6663
0.1614 6.0 300 1.5295 0.71 0.6736 0.6543 0.6423
0.1129 7.0 350 2.1055 0.71 0.6779 0.6413 0.6511
0.098 8.0 400 1.9579 0.705 0.6697 0.6558 0.6601
0.0479 9.0 450 2.0535 0.72 0.6794 0.6663 0.6711
0.0173 10.0 500 2.5381 0.7 0.6838 0.6604 0.6608
0.0308 11.0 550 2.4592 0.735 0.7014 0.6851 0.6901
0.0265 12.0 600 2.3131 0.725 0.6910 0.6845 0.6849
0.016 13.0 650 2.4025 0.74 0.7035 0.6915 0.6949
0.013 14.0 700 2.3933 0.745 0.7070 0.6831 0.6909
0.016 15.0 750 2.6819 0.725 0.7006 0.6738 0.6759
0.0126 16.0 800 2.3679 0.74 0.7050 0.6839 0.6898
0.0023 17.0 850 2.5252 0.745 0.7119 0.6880 0.6933
0.01 18.0 900 2.5598 0.74 0.7056 0.6828 0.6906
0.0093 19.0 950 2.4353 0.745 0.7057 0.6922 0.6974
0.0039 20.0 1000 2.4223 0.75 0.7128 0.6998 0.7043

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu116
  • Tokenizers 0.13.2
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