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

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Salvatore/
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: 1.4025
Accuracy: 0.2237

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-06
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: 480

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3855	1.0	25	1.3973	0.275
1.4151	2.0	50	1.4034	0.1875
1.4342	3.0	75	1.4028	0.2
1.4189	4.0	100	1.3967	0.1625
1.3925	5.0	125	1.4030	0.2375
1.406	6.0	150	1.3974	0.1875
1.3868	7.0	175	1.4011	0.175
1.3969	8.0	200	1.4019	0.15
1.4233	9.0	225	1.3985	0.2125
1.4011	10.0	250	1.4081	0.25
1.3994	11.0	275	1.4037	0.175
1.3945	12.0	300	1.4094	0.2625
1.3844	13.0	325	1.4050	0.175
1.378	14.0	350	1.4081	0.275
1.3965	15.0	375	1.4095	0.275
1.3982	16.0	400	1.4116	0.275
1.385	17.0	425	1.4114	0.275
1.3735	18.0	450	1.4103	0.275
1.3817	19.0	475	1.4106	0.275
1.3785	19.2	480	1.4106	0.275

Framework versions

Transformers 4.44.1
Pytorch 2.4.0
Datasets 2.19.1
Tokenizers 0.19.1