videomae-base-readminds-assignment – AI Model by LinStevenn | AlphaNeural AI

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videomae-base-readminds-assignment

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video-classification

generated_from_trainer

MCG-NJU/videomae-base

endpoints_compatible

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videomae-base-readminds-assignment

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: 1.5827

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: 2
eval_batch_size: 2
seed: 42
optimizer: Use 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: 0.1
training_steps: 100

Training results

Training Loss	Epoch	Step	Validation Loss
1.5236	0.12	12	1.4575
1.1957	1.12	24	1.4403
0.7669	2.12	36	1.4573
0.4632	3.12	48	1.5034
0.299	4.12	60	1.5987
0.1672	5.12	72	1.5975
0.0682	6.12	84	1.5670
0.0324	7.12	96	1.5827
0.0155	8.04	100	1.5827

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.0