pretoxtm-sentence-classifier

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pretoxtm-sentence-classifier

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on javicorvi/pretoxtm-dataset. It achieves the following results on the evaluation set:

• Loss: 0.1181
• Precision: 0.9788
• Recall: 0.9800
• Accuracy: 0.9795
• F1: 0.9794

Model description

PretoxTM Sentence Classifier is a model trained on preclinical toxicology literature, designed to detect sentences that contain treatment-related findings.

Training and evaluation data

The model was trained on javicorvi/pretoxtm-dataset.

The dataset is divided in train, validation and test.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1.1848183151867784e-05
• train_batch_size: 4
• eval_batch_size: 8
• seed: 1
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2