b3r-test – AI Model by cp-gustavo | AlphaNeural AI

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cp-gustavo/
b3r-test

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token-classification

generated_from_trainer

dmis-lab/biobert-v1.1

endpoints_compatible

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b3r-test

This model is a fine-tuned version of dmis-lab/biobert-v1.1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.6586
Precision: 0.5839
Recall: 0.6450
F1: 0.6129

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: 0.00012839450868399685
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: 0.1685473261668876
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
1.0701	1.0	330	0.5494	0.5424	0.5540	0.5482
0.4877	2.0	660	0.5052	0.5561	0.6069	0.5804
0.3423	3.0	990	0.5166	0.5772	0.6301	0.6025
0.2322	4.0	1320	0.5577	0.5766	0.6386	0.6060
0.1555	5.0	1650	0.6107	0.5842	0.6423	0.6118
0.1063	6.0	1980	0.6586	0.5839	0.6450	0.6129

Framework versions

Transformers 4.51.1
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1