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videomae-base-finetuned-dd – AI Model by RodrigoFardin | AlphaNeural AI
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RodrigoFardin
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videomae-base-finetuned-dd
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transformers
tensorboard
safetensors
videomae
video-classification
generated_from_trainer
MCG-NJU/videomae-base
finetune
cc-by-nc-4.0
endpoints_compatible
us
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videomae-base-finetuned-dd
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: 0.4577
Accuracy: 0.8909
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: 2
eval_batch_size: 2
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: 1352
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5777
0.2485
336
0.8214
0.8373
1.144
1.2493
673
0.4453
0.8754
0.2783
2.2493
1010
0.8930
0.8171
0.0037
3.2470
1344
0.4077
0.8979
0.2113
4.0059
1352
0.4079
0.8979
Framework versions
Transformers 4.40.2
Pytorch 1.12.0+cu113
Datasets 2.19.1
Tokenizers 0.19.1
