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all-mpnet-base-v2-20240102

This model is a fine-tuned version of sentence-transformers/all-mpnet-base-v2 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1930
  • F1: 0.7429
  • Roc Auc: 0.8143
  • Accuracy: 0.6406

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 11

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
No log 1.0 109 0.3929 0.0 0.5 0.0
No log 2.0 218 0.3159 0.0 0.5 0.0
No log 3.0 327 0.2721 0.5170 0.6766 0.3564
No log 4.0 436 0.2410 0.6267 0.7382 0.4854
0.3349 5.0 545 0.2238 0.6389 0.7415 0.4889
0.3349 6.0 654 0.2115 0.6564 0.7538 0.5156
0.3349 7.0 763 0.2005 0.6985 0.7824 0.5749
0.3349 8.0 872 0.1930 0.7429 0.8143 0.6406
0.3349 9.0 981 0.1903 0.7413 0.8161 0.6461
0.1716 10.0 1090 0.1879 0.7379 0.8170 0.6500
0.1716 11.0 1199 0.1879 0.7359 0.8141 0.6431

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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