task2_active_drug – AI Model by Luggi | AlphaNeural AI

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Luggi/
task2_active_drug

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token-classification

generated_from_trainer

GerMedBERT/medbert-512

autotrain_compatible

endpoints_compatible

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task2_active_drug

This model is a fine-tuned version of GerMedBERT/medbert-512 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0195
Precision: 0.7571
Recall: 0.9382
F1: 0.8380
Accuracy: 0.9960

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
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
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	330	0.0115	0.7773	0.9148	0.8405	0.9963
0.0622	2.0	660	0.0161	0.7436	0.9298	0.8264	0.9958
0.0622	3.0	990	0.0159	0.7512	0.9382	0.8343	0.9960
0.009	4.0	1320	0.0174	0.7610	0.9337	0.8385	0.9962
0.0041	5.0	1650	0.0195	0.7571	0.9382	0.8380	0.9960

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.2