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dog_emotion_v3_resnet – AI Model by Dewa | AlphaNeural AI
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Dewa
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dog_emotion_v3_resnet
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transformers
pytorch
tensorboard
resnet
image-classification
generated_from_trainer
microsoft/resnet-50
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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dog_emotion_v3_resnet
This model is a fine-tuned version of
microsoft/resnet-50
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.3063
Accuracy: 0.5075
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: 5.5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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
1.0
50
1.3721
0.3475
No log
2.0
100
1.3502
0.45
No log
3.0
150
1.3292
0.485
No log
4.0
200
1.3103
0.5025
No log
5.0
250
1.3063
0.5075
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.0
Tokenizers 0.13.3
