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multiCorp_cut_5e-05_250
This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0722
- Precision: 0.7331
- Recall: 0.6101
- F1: 0.6660
- Accuracy: 0.9851
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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1500
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.2942 | 0.66 | 50 | 0.0969 | 0.4120 | 0.1031 | 0.1649 | 0.9742 |
0.0781 | 1.32 | 100 | 0.0720 | 0.4497 | 0.2933 | 0.3551 | 0.9779 |
0.0673 | 1.97 | 150 | 0.0632 | 0.5067 | 0.4227 | 0.4609 | 0.9794 |
0.046 | 2.63 | 200 | 0.0617 | 0.5822 | 0.4780 | 0.5250 | 0.9814 |
0.0426 | 3.29 | 250 | 0.0607 | 0.6815 | 0.5033 | 0.5790 | 0.9833 |
0.0365 | 3.95 | 300 | 0.0596 | 0.6222 | 0.5558 | 0.5871 | 0.9823 |
0.026 | 4.61 | 350 | 0.0632 | 0.6341 | 0.6026 | 0.6180 | 0.9829 |
0.0224 | 5.26 | 400 | 0.0700 | 0.6951 | 0.5576 | 0.6188 | 0.9838 |
0.0197 | 5.92 | 450 | 0.0621 | 0.6834 | 0.5989 | 0.6384 | 0.9840 |
0.0147 | 6.58 | 500 | 0.0676 | 0.7181 | 0.6064 | 0.6575 | 0.9845 |
0.0119 | 7.24 | 550 | 0.0689 | 0.6965 | 0.6560 | 0.6757 | 0.9846 |
0.0106 | 7.89 | 600 | 0.0722 | 0.7331 | 0.6101 | 0.6660 | 0.9851 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2