readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: videomae-base-short-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-k
    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-short-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-k
  
  This model is a fine-tuned version of [MCG-NJU/videomae-base-short-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-short-finetuned-kinetics) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0855
  - Accuracy: 0.6764
  
  ## 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.3699        | 0.06  | 200  | 0.2920          | 0.8925   |
  | 0.3127        | 1.06  | 400  | 0.6035          | 0.77     |
  | 0.2864        | 2.06  | 600  | 0.5088          | 0.8237   |
  | 0.1739        | 3.06  | 800  | 0.6310          | 0.765    |
  | 0.1835        | 4.06  | 1000 | 0.3643          | 0.8738   |
  | 0.1075        | 5.06  | 1200 | 0.3455          | 0.8862   |
  | 0.1362        | 6.06  | 1400 | 0.9145          | 0.75     |
  | 0.2958        | 7.06  | 1600 | 0.3544          | 0.895    |
  | 0.1571        | 8.06  | 1800 | 0.3748          | 0.8912   |
  | 0.2448        | 9.06  | 2000 | 0.3646          | 0.8975   |
  | 0.1939        | 10.06 | 2200 | 0.4430          | 0.8762   |
  | 0.0666        | 11.06 | 2400 | 0.4916          | 0.8762   |
  | 0.1958        | 12.06 | 2600 | 0.5114          | 0.8638   |
  | 0.1063        | 13.06 | 2800 | 0.5701          | 0.8612   |
  | 0.1047        | 14.06 | 3000 | 0.5226          | 0.8688   |
  | 0.0131        | 15.06 | 3200 | 0.4656          | 0.8812   |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  