disease_detector_1.5B – AI Model by Jeongmoon | AlphaNeural AI

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disease_detector_1.5B

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Qwen/Qwen2.5-1.5B-Instruct

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disease_detector_1.5B

This model is a fine-tuned version of Qwen/Qwen2.5-1.5B-Instruct on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2099
Accuracy: 0.9328
Roc Auc: 0.9572

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: 1e-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: 7

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss	Roc Auc
No log	1.0	231	0.7950	0.4443	0.8136
No log	2.0	462	0.7981	0.5223	0.8526
0.4264	3.0	693	0.7981	0.6139	0.8819
0.4264	4.0	924	0.8385	0.5812	0.8891
0.1589	5.0	1130	0.2099	0.9328	0.9572
0.1589	6.0	1356	0.2449	0.9104	0.9562
0.1441	7.0	1582	0.2488	0.9129	0.9544

Framework versions

PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.6.0+cu124
Datasets 4.2.0
Tokenizers 0.22.1