Chaitanya798800/videomae-large_Sports_action_recognition_5

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videomae-largeSportsactionrecognition5

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: 0.0454
• —evalconfusionmatrix: {'confusion_matrix': array([[24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [ 0, 39, 0, 0, 0, 0, 0, 0, 0, 0, 1], [ 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], [ 1, 0, 0, 0, 0, 0, 0, 0, 0, 14, 0], [ 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 33]])}
• —eval_runtime: 123.4171
• —evalsamplesper_second: 3.095
• —evalstepsper_second: 1.548
• —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
• —trainbatchsize: 2
• —evalbatchsize: 2
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_ratio: 0.1
• —training_steps: 2744

Framework versions

• —Transformers 4.39.3
• —Pytorch 2.2.1+cu121
• —Datasets 2.18.0
• —Tokenizers 0.15.2