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
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Model tree for mikeslin/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base