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metadata
library_name: transformers
license: apache-2.0
base_model: sentence-transformers/all-mpnet-base-v2
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: Hub-Report-20241130161450
    results: []

Hub-Report-20241130161450

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: 0.0618
  • F1: 0.9067
  • Roc Auc: 0.9492
  • Accuracy: 0.9023

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 13

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
0.315 1.0 502 0.2049 0.0 0.5 0.0
0.1619 2.0 1004 0.1230 0.7725 0.8300 0.6651
0.0952 3.0 1506 0.0808 0.9009 0.9401 0.8878
0.0607 4.0 2008 0.0725 0.8861 0.9350 0.8797
0.0427 5.0 2510 0.0612 0.9017 0.9461 0.8983
0.0307 6.0 3012 0.0619 0.8948 0.9418 0.8907
0.0247 7.0 3514 0.0629 0.8983 0.9437 0.8930
0.0195 8.0 4016 0.0633 0.8979 0.9442 0.8953
0.017 9.0 4518 0.0603 0.9052 0.9480 0.9017
0.0149 10.0 5020 0.0633 0.9022 0.9462 0.9
0.0137 11.0 5522 0.0619 0.9040 0.9474 0.9017
0.0127 12.0 6024 0.0616 0.9042 0.9482 0.8994
0.0121 13.0 6526 0.0618 0.9067 0.9492 0.9023

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3