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chord_ViT-finetuned – AI Model by aliciiavs | AlphaNeural AI
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aliciiavs
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chord_ViT-finetuned
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
google/vit-base-patch16-224
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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chord_ViT-finetuned
This model is a fine-tuned version of
google/vit-base-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.0093
Accuracy: 0.2111
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.2079
0.94
12
2.1573
0.15
2.0732
1.96
25
2.0678
0.1778
1.9993
2.82
36
2.0093
0.2111
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
