marker-associations-snp-binary-base

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the marker-associations-snp-binary-base dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4027
  • Precision: 0.9384
  • Recall: 0.9056
  • F1: 0.9217
  • Accuracy: 0.9108
  • Auc: 0.9578

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: 16
  • eval_batch_size: 16
  • seed: 1
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy Auc
No log 1.0 153 0.2776 0.9 0.9441 0.9215 0.9067 0.9613
No log 2.0 306 0.4380 0.9126 0.9126 0.9126 0.8986 0.9510
No log 3.0 459 0.4027 0.9384 0.9056 0.9217 0.9108 0.9578
0.2215 4.0 612 0.3547 0.9449 0.8986 0.9211 0.9108 0.9642
0.2215 5.0 765 0.4465 0.9107 0.9266 0.9185 0.9047 0.9636
0.2215 6.0 918 0.5770 0.8970 0.9441 0.9199 0.9047 0.9666

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.9.0+cu111
  • Tokenizers 0.10.3
Downloads last month
5
Hosted inference API
Text Classification
Examples
Examples
Mask token: [MASK]
This model can be loaded on the Inference API on-demand.
Evaluation results