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OTAR3088/
CeLLaTe-ner-2class-pubmedbert-baseline

Name: CeLLaTe-ner-2class-pubmedbert-baseline
Availability: InStock

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CeLLaTe-ner-pubmedbert-baseline

This model is a fine-tuned version of microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext on the OTAR3088/CeLLaTe_V3.2_contracted_ent_IOB dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 3407
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.01
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.2418	1.0	263	0.0612	0.6099	0.7212	0.6609	0.9794
0.0403	2.0	526	0.0520	0.7575	0.7224	0.7395	0.9834
0.0258	3.0	789	0.0613	0.7419	0.7401	0.7410	0.9829
0.0196	4.0	1052	0.0644	0.7746	0.7254	0.7492	0.9839
0.0145	5.0	1315	0.0683	0.7746	0.7047	0.7380	0.9831
0.011	6.0	1578	0.0768	0.7628	0.7084	0.7346	0.9831
0.0086	7.0	1841	0.0732	0.7468	0.7450	0.7459	0.9838