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clinical_trial_stop_reasons_custom

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1448
  • Accuracy Thresh: 0.9570
  • F1 Micro: 0.5300
  • F1 Macro: 0.1254
  • Confusion Matrix: [[5940 15] [ 270 150]]

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: 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: 7

Training results

Training Loss Epoch Step Validation Loss Accuracy Thresh F1 Micro F1 Macro Confusion Matrix
No log 1.0 106 0.2812 0.8328 0.0 0.0 [[5955 0]
[ 420 0]]
No log 2.0 212 0.2189 0.9382 0.0 0.0 [[5955 0]
[ 420 0]]
No log 3.0 318 0.1840 0.9489 0.0 0.0 [[5955 0]
[ 420 0]]
No log 4.0 424 0.1638 0.9485 0.4940 0.0989 [[5943 12]
[ 288 132]]
0.239 5.0 530 0.1526 0.9533 0.5060 0.1018 [[5943 12]
[ 277 143]]
0.239 6.0 636 0.1467 0.9564 0.5077 0.1020 [[5938 17]
[ 275 145]]
0.239 7.0 742 0.1448 0.9570 0.5300 0.1254 [[5940 15]
[ 270 150]]

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.12.1+cu102
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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