readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  - video-classification
  - videomae
  - vision
  metrics:
  - accuracy
  model-index:
  - name: videomae-base-finetuned-ucf101-subset
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # videomae-base-finetuned-ucf101-subset
  
  This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3992
  - Accuracy: 0.8645
  
  ## 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: 148
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.1374        | 0.26  | 38   | 1.7413          | 0.5714   |
  | 0.7949        | 1.26  | 76   | 0.7747          | 0.8      |
  | 0.4279        | 2.26  | 114  | 0.4053          | 0.9143   |
  | 0.291         | 3.23  | 148  | 0.3429          | 0.9286   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  