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VideoMAE-Test – AI Model by darkviid | AlphaNeural AI
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darkviid
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VideoMAE-Test
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tensorboard
safetensors
videomae
generated_from_trainer
MCG-NJU/videomae-base
finetune
cc-by-nc-4.0
us
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VideoMAE-Test
This model is a fine-tuned version of
MCG-NJU/videomae-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.7697
Accuracy: 0.6742
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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 1160
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.6841
1.0
1160
1.7697
0.6742
Framework versions
Transformers 4.38.0.dev0
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1
