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chord-final-model – AI Model by aliciiavs | AlphaNeural AI
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aliciiavs
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chord-final-model
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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-final-model
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: 1.2133
Accuracy: 0.695
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: 7
total_train_batch_size: 224
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.98
8
1.5147
0.4
1.6354
1.96
16
1.3898
0.585
1.4272
2.95
24
1.2960
0.67
1.2884
3.93
32
1.2369
0.67
1.2176
4.91
40
1.2133
0.695
Framework versions
Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2
