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swin-tiny-patch4-window7-224-finetuned-birds-finetuned-birds – AI Model by gjuggler | AlphaNeural AI
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gjuggler
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swin-tiny-patch4-window7-224-finetuned-birds-finetuned-birds
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transformers
pytorch
tensorboard
swin
image-classification
generated_from_trainer
bird-data
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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swin-tiny-patch4-window7-224-finetuned-birds-finetuned-birds
This model is a fine-tuned version of
gjuggler/swin-tiny-patch4-window7-224-finetuned-birds
on the bird-data dataset. It achieves the following results on the evaluation set:
Loss: 1.2646
Accuracy: 0.6919
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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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
2.0629
1.0
84
1.5111
0.6455
1.8561
2.0
168
1.3206
0.6747
1.686
3.0
252
1.2646
0.6919
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
