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metadata
library_name: transformers
license: apache-2.0
base_model: sandeshrajx/bert-fraud-classification-test-mass
tags:
  - generated_from_trainer
metrics:
  - f1
  - precision
model-index:
  - name: bert-fraud-classification-test-mass-4
    results: []

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bert-fraud-classification-test-mass-4

This model is a fine-tuned version of sandeshrajx/bert-fraud-classification-test-mass on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3408
  • F1: 0.8508
  • Precision: 0.8627
  • Val Accuracy: 0.8663

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: 44
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 88
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Precision Val Accuracy
0.3874 0.1743 40 0.3197 0.8579 0.8936 0.8758
0.3614 0.3486 80 0.3427 0.8382 0.8846 0.8603
0.3563 0.5229 120 0.3505 0.8435 0.8468 0.8584
0.4263 0.6972 160 0.3407 0.8454 0.8589 0.8617
0.3514 0.8715 200 0.3473 0.8413 0.8421 0.8560
0.259 1.0458 240 0.3378 0.8417 0.9106 0.8663
0.3148 1.2200 280 0.3543 0.8479 0.8889 0.8679
0.2685 1.3943 320 0.3507 0.8501 0.9040 0.8715
0.2271 1.5686 360 0.3773 0.8406 0.8262 0.8526
0.376 1.7429 400 0.3412 0.8520 0.8731 0.8687
0.2739 1.9172 440 0.3408 0.8508 0.8627 0.8663

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.1