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ecg-classifier-v2-balanced – AI Model by MMM0003 | AlphaNeural AI
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MMM0003
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ecg-classifier-v2-balanced
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transformers
safetensors
vit
image-classification
generated_from_trainer
google/vit-base-patch16-224-in21k
finetune
apache-2.0
endpoints_compatible
us
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ecg-classifier-v2-balanced
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.3650
Accuracy: 0.44
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: 0.0002
train_batch_size: 32
eval_batch_size: 16
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: linear
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.5014
2.0
100
1.5052
0.2825
1.4310
4.0
200
1.3650
0.44
Framework versions
Transformers 5.2.0
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
