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disease_detector – AI Model by Jeongmoon | AlphaNeural AI
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Jeongmoon
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disease_detector
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peft
safetensors
adapter
lora
transformers
Qwen/Qwen2.5-1.5B-Instruct
apache-2.0
us
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Model card
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disease_detector
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: 0.3195
Accuracy: 0.8897
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: 5
Training results
Training Loss
Epoch
Step
Accuracy
Validation Loss
No log
1.0
224
0.7793
0.4380
No log
2.0
448
0.8427
0.3526
0.5211
3.0
672
0.8662
0.3445
0.5211
4.0
896
0.8897
0.3195
0.199
5.0
1120
0.8873
0.3450
Framework versions
PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.6.0+cu124
Datasets 4.2.0
Tokenizers 0.22.1
