STS-conventional-Fine-Tuning-Capstone-roberta-base-filtered-160

This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2762
  • Accuracy: 0.7247

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: 3e-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
No log 1.0 113 0.7940 0.6610
No log 2.0 226 0.7463 0.6929
No log 3.0 339 0.9240 0.7041
No log 4.0 452 0.9070 0.6629
0.5167 5.0 565 1.1376 0.7022
0.5167 6.0 678 1.2043 0.7022
0.5167 7.0 791 1.3083 0.7228
0.5167 8.0 904 1.5205 0.7154
0.1626 9.0 1017 1.5875 0.7154
0.1626 10.0 1130 1.8172 0.7041
0.1626 11.0 1243 1.9300 0.7154
0.1626 12.0 1356 1.8632 0.7247
0.1626 13.0 1469 2.0908 0.7135
0.0655 14.0 1582 2.0766 0.7191
0.0655 15.0 1695 2.2582 0.7135
0.0655 16.0 1808 2.2743 0.7154
0.0655 17.0 1921 2.2310 0.7228
0.0237 18.0 2034 2.2574 0.7285
0.0237 19.0 2147 2.2768 0.7266
0.0237 20.0 2260 2.2762 0.7247

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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