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3class_EfficientNetv2_ForTesting – AI Model by MinhLe999 | AlphaNeural AI
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3class_EfficientNetv2_ForTesting
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image-classification
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3class_EfficientNetv2_ForTesting
This model is a fine-tuned version of
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.1331
eval_model_preparation_time: 0.0183
eval_precision: 0.9637
eval_recall: 0.9679
eval_accuracy: 0.9712
eval_f1: 0.9656
eval_roc_auc: 0.9966
eval_runtime: 62.5585
eval_samples_per_second: 18.303
eval_steps_per_second: 0.575
epoch: 0.3106
step: 200
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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 2
mixed_precision_training: Native AMP
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
