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

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Siccimo/
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: 0.2617
Accuracy: 0.9097

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: 16
eval_batch_size: 16
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: 148

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.0115	0.1284	19	1.5469	0.5429
1.2145	1.1284	38	0.9201	0.7
0.6166	2.1284	57	0.5548	0.8286
0.3255	3.1284	76	0.3556	0.9
0.1945	4.1284	95	0.2918	0.8857
0.098	5.1284	114	0.3874	0.8714
0.0571	6.1284	133	0.1540	0.9571
0.0387	7.1014	148	0.2547	0.8571

Framework versions

Transformers 4.42.3
Pytorch 2.1.2
Datasets 2.20.0
Tokenizers 0.19.1