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ecg-classifier – AI Model by MMM0003 | AlphaNeural AI
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MMM0003
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ecg-classifier
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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
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: 1.3378
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: 10
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.5029
2.0
100
1.5073
0.2825
1.3914
4.0
200
1.3344
0.4125
1.4682
6.0
300
1.3903
0.4125
1.3581
8.0
400
1.3351
0.44
1.3528
10.0
500
1.3378
0.44
Framework versions
Transformers 5.2.0
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
