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videomae-large_ActionRecognition – AI Model by Chaitanya798800 | AlphaNeural AI
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Chaitanya798800
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videomae-large_ActionRecognition
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transformers
safetensors
videomae
video-classification
generated_from_trainer
MCG-NJU/videomae-large
finetune
cc-by-nc-4.0
endpoints_compatible
us
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videomae-large_ActionRecognition
This model is a fine-tuned version of
MCG-NJU/videomae-large
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.0503
eval_confusion_matrix: {'confusion_matrix': array([[14, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 12, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 17, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 23, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 5, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 1, 32, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 10, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 12, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 7, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 22]])}
eval_runtime: 27.1769
eval_samples_per_second: 5.703
eval_steps_per_second: 2.87
step: 0
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: 900
Framework versions
Transformers 4.39.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
