videomae-base-finetuned-cropped-shooting-and-layup-dataset – AI Model by Babaili | AlphaNeural AI

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Babaili/
videomae-base-finetuned-cropped-shooting-and-layup-dataset

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video-classification

generated_from_trainer

endpoints_compatible

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videomae-base-finetuned-cropped-shooting-and-layup-dataset

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: 0.5361
Accuracy: 0.6667

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.1	5	0.6288	0.75
0.4089	1.1	10	0.7199	0.75
0.4089	2.1	15	0.7932	0.75
0.3801	3.1	20	0.7371	0.75
0.3801	4.1	25	0.8587	0.75
0.3258	5.1	30	0.7767	0.75
0.3258	6.1	35	0.7317	0.75
0.2265	7.1	40	0.7253	0.75
0.2265	8.1	45	0.7179	0.75
0.2107	9.1	50	0.7268	0.75

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3