videomae-base-finetuned-ucf101-subset – AI Model by sagniksengupta | AlphaNeural AI

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sagniksengupta/
videomae-base-finetuned-ucf101-subset

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video-classification

generated_from_trainer

MCG-NJU/videomae-base

endpoints_compatible

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videomae-base-finetuned-ucf101-subset

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: 0.0986
Accuracy: 0.9784

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.05
training_steps: 2280

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8511	0.1254	286	1.3736	0.5602
0.7099	1.1254	572	0.5359	0.8397
0.3433	2.1254	858	0.4332	0.8772
0.2015	3.1254	1144	0.2627	0.9203
0.1166	4.1254	1430	0.1257	0.9620
0.0394	5.1254	1716	0.0980	0.9714
0.0092	6.1254	2002	0.0888	0.9766
0.0246	7.1219	2280	0.0739	0.9822

Framework versions

Transformers 4.52.2
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1