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videomae-surf-analytics-v4 – AI Model by 2nzi | AlphaNeural AI

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2nzi/
videomae-surf-analytics-v4

like

0

video-classification

generated_from_trainer

MCG-NJU/videomae-base

endpoints_compatible

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videomae-surf-analytics-runpod7

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:

eval_loss: 0.5278
eval_accuracy: 0.9180
eval_f1: 0.9179
eval_runtime: 73.3325
eval_samples_per_second: 1.664
eval_steps_per_second: 0.218
epoch: 5.0024
step: 8857

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: 9200

Framework versions

Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1