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weather-mod – AI Model by ChasingMercer | AlphaNeural AI
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ChasingMercer
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weather-mod
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transformers
pytorch
tensorboard
beit
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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weather-mod
This model is a fine-tuned version of
microsoft/beit-base-patch16-224-pt22k-ft22k
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 0.0907
Accuracy: 0.9745
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4096
1.0
118
0.3402
0.8790
0.2749
2.0
236
0.1482
0.9490
0.1989
3.0
354
0.1297
0.9660
0.1129
4.0
472
0.1074
0.9788
0.0827
5.0
590
0.1023
0.9745
0.0644
6.0
708
0.0907
0.9745
Framework versions
Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2
