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metadata
license: cc-by-nc-4.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-short-finetuned-ssv2-finetuned-rwf2000-epochs8-batch8-fp16
    results: []

videomae-base-short-finetuned-ssv2-finetuned-rwf2000-epochs8-batch8-fp16

This model is a fine-tuned version of MCG-NJU/videomae-base-short-finetuned-ssv2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4339
  • Accuracy: 0.4643

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 3200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.4239 0.06 200 0.3879 0.82
0.4179 1.06 400 1.1635 0.6162
0.4329 2.06 600 0.8215 0.63
0.3051 3.06 800 0.5541 0.7412
0.172 4.06 1000 0.4696 0.8363
0.1955 5.06 1200 0.5384 0.78
0.2301 6.06 1400 1.3358 0.635
0.2995 7.06 1600 1.0372 0.7087
0.3789 8.06 1800 0.8670 0.7412
0.2525 9.06 2000 0.5886 0.8225
0.1846 10.06 2200 0.7851 0.735
0.1547 11.06 2400 0.8905 0.7638
0.2501 12.06 2600 0.9807 0.76
0.1046 13.06 2800 1.0419 0.7438
0.0786 14.06 3000 1.0128 0.7538
0.0178 15.06 3200 1.0156 0.75

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2