deberta med ner 2 This model is a fine tuned version of DeBERTa on the PubMED Dataset. Model description Medical NER Model finetuned on BERT to recognize 41 Medical entities. Training hyperparameters The following hyperparameters were used during training: learning rate: 2e 05 train batch size: 8 eval batch size: 16 seed: 42 gradient accumulation steps: 2 total train batch size: 16 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: cosine lr scheduler warmup ratio: 0.1 num epochs: 30 mixed precision training: Native AMP Usage The easiest way is to load the inference api from huggingface and second method is through the pipeline object offered by transformers library. Author Author: Saketh Mattupalli Framework versions Transformers 4.37.0 Pytorch 2.1.2 Datasets 2.1.0 Tokenizers 0.15.1
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