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cold_reman_gpu_v1

This model is a fine-tuned version of ibm/ColD-Fusion on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4520
  • F1: 0.6592
  • Roc Auc: 0.7559
  • Recall: 0.6197
  • Precision: 0.704

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Recall Precision
No log 1.0 452 0.4556 0.6 0.7160 0.5282 0.6944
0.4832 2.0 904 0.4520 0.6592 0.7559 0.6197 0.704
0.3505 3.0 1356 0.4658 0.6543 0.7530 0.6197 0.6929

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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