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beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-6e-05 – AI Model by lixiqi | AlphaNeural AI
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lixiqi
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beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-6e-05
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transformers
pytorch
tensorboard
beit
image-classification
generated_from_trainer
image_folder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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beit-base-patch16-224-pt22k-ft22k-finetuned-FER2013-6e-05
This model is a fine-tuned version of
microsoft/beit-base-patch16-224-pt22k-ft22k
on the image_folder dataset. It achieves the following results on the evaluation set:
Loss: 0.8551
Accuracy: 0.6863
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: 6e-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
1.1611
1.0
224
0.9904
0.6278
1.0324
2.0
448
0.9066
0.6666
0.9725
3.0
672
0.8551
0.6863
Framework versions
Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1
