PubMedBERT MNLI MedNLI This model is a fine tuned version of PubMedBERT on the MNLI dataset first and then on the MedNLI dataset. It achieves the following results on the evaluation set: Loss: 0.9501 Accuracy: 0.8667 Model description More information needed Intended uses & limitations The model can be used for NLI tasks related to biomedical data and even be adapted to fact checking tasks. It can be used from the Huggingface pipeline method as follows: The output for the above will be: 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: 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: 20.0 Training results Training Loss Epoch Step Validation Loss Accuracy : : : : : : : : : : 0.5673 1.42 500 0.4358 0.8437 0.2898 2.85 1000 0.4845 0.8523 0.1669 4.27 1500 0.6233 0.8573 0.1087 5.7 2000 0.7263 0.8573 0.0728 7.12 2500 0.8841 0.8638 0.0512 8.55 3000 0.9501 0.8667 0.0372 9.97 3500 1.0440 0.8566 0.0262 11.4 4000 1.0770 0.8609 0.0243 12.82 4500 1.0931 0.8616 0.023 14.25 5000 1…
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