videomae-base-finetuned-ucf101-subset

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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:

• eval_loss: 2.2686
• eval_accuracy: 0.1548
• eval_runtime: 168.437
• eval_samples_per_second: 0.92
• eval_steps_per_second: 0.03
• epoch: 0
• step: 0

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: 32
• eval_batch_size: 32
• 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

Framework versions

• Transformers 4.31.0
• Pytorch 2.2.1
• Datasets 2.12.0
• Tokenizers 0.13.3