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fer_plus_V2 – AI Model by ricardoSLabs | AlphaNeural AI
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fer_plus_V2
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transformers
tensorboard
safetensors
beit
image-classification
generated_from_trainer
imagefolder
microsoft/beit-base-patch16-224-pt22k-ft22k
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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fer_plus_V2
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: 0.7483
Accuracy: 0.7598
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.0697
1.0
222
1.0167
0.6354
0.7784
2.0
444
0.8059
0.7124
0.5911
3.0
666
0.7499
0.7384
0.4609
4.0
888
0.7586
0.7502
0.3712
5.0
1110
0.7483
0.7598
Framework versions
Transformers 4.47.0
Pytorch 2.5.1+cu121
Datasets 3.3.1
Tokenizers 0.21.0
