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videomae-large_Sports_action_recognition – AI Model by Chaitanya798800 | AlphaNeural AI
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Chaitanya798800
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videomae-large_Sports_action_recognition
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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_Sports_action_recognition
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: 0.0027
eval_confusion_matrix: {'confusion_matrix': array([[24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 40, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 28, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 37, 0, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 43, 0, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 72, 0, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 28, 0, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 33, 0, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 26, 0, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 15, 0], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 36]])}
eval_runtime: 127.0184
eval_samples_per_second: 3.007
eval_steps_per_second: 1.504
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: 17150
Framework versions
Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
