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resnet-50-finetuned-memes-v2 – AI Model by jayanta | AlphaNeural AI
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resnet-50-finetuned-memes-v2
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transformers
pytorch
tensorboard
resnet
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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resnet-50-finetuned-memes-v2
This model is a fine-tuned version of
microsoft/resnet-50
on the imagefolder dataset. It achieves the following results on the evaluation set:
Loss: 1.3295
Accuracy: 0.4567
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: 0.00012
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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.4954
0.99
20
1.4559
0.4567
1.407
1.99
40
1.3772
0.4567
1.3744
2.99
60
1.3378
0.4567
1.3427
3.99
80
1.3295
0.4567
Framework versions
Transformers 4.24.0.dev0
Pytorch 1.11.0+cu102
Datasets 2.6.1.dev0
Tokenizers 0.13.1
