readme: ---
  license: cc-by-nc-4.0
  tags:
  - generated_from_trainer
  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: 0.2709
  - Accuracy: 0.9540
  
  ## 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: 4
  - eval_batch_size: 4
  - 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: 3750
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.2549        | 0.02  | 75   | 2.2707          | 0.0270   |
  | 1.7546        | 1.02  | 150  | 1.8893          | 0.3514   |
  | 0.8462        | 2.02  | 225  | 0.8723          | 0.6216   |
  | 0.551         | 3.02  | 300  | 0.4068          | 0.8108   |
  | 0.6627        | 4.02  | 375  | 0.6916          | 0.7297   |
  | 0.4383        | 5.02  | 450  | 0.5512          | 0.7568   |
  | 0.3398        | 6.02  | 525  | 0.4060          | 0.8378   |
  | 0.0769        | 7.02  | 600  | 0.8299          | 0.8108   |
  | 0.0077        | 8.02  | 675  | 0.0570          | 0.9730   |
  | 0.0055        | 9.02  | 750  | 0.0168          | 1.0      |
  | 0.002         | 10.02 | 825  | 0.0497          | 0.9730   |
  | 0.1242        | 11.02 | 900  | 0.2132          | 0.9459   |
  | 0.0022        | 12.02 | 975  | 0.0026          | 1.0      |
  | 0.0074        | 13.02 | 1050 | 0.0577          | 0.9730   |
  | 0.0038        | 14.02 | 1125 | 0.0137          | 1.0      |
  | 0.0011        | 15.02 | 1200 | 0.0022          | 1.0      |
  | 0.001         | 16.02 | 1275 | 0.0025          | 1.0      |
  | 0.0009        | 17.02 | 1350 | 0.0059          | 1.0      |
  | 0.0024        | 18.02 | 1425 | 0.1411          | 0.9730   |
  | 0.1709        | 19.02 | 1500 | 0.0041          | 1.0      |
  | 0.0008        | 20.02 | 1575 | 0.0489          | 0.9730   |
  | 0.0007        | 21.02 | 1650 | 0.0116          | 1.0      |
  | 0.0008        | 22.02 | 1725 | 0.0741          | 0.9730   |
  | 0.0008        | 23.02 | 1800 | 0.1699          | 0.9730   |
  | 0.0007        | 24.02 | 1875 | 0.1828          | 0.9730   |
  | 0.0006        | 25.02 | 1950 | 0.1652          | 0.9730   |
  | 0.0006        | 26.02 | 2025 | 0.1608          | 0.9730   |
  | 0.0005        | 27.02 | 2100 | 0.1595          | 0.9730   |
  | 0.0005        | 28.02 | 2175 | 0.1445          | 0.9730   |
  | 0.0006        | 29.02 | 2250 | 0.1488          | 0.9730   |
  | 0.0005        | 30.02 | 2325 | 0.1202          | 0.9730   |
  | 0.0005        | 31.02 | 2400 | 0.1238          | 0.9730   |
  | 0.0004        | 32.02 | 2475 | 0.1225          | 0.9730   |
  | 0.0005        | 33.02 | 2550 | 0.2320          | 0.9459   |
  | 0.0004        | 34.02 | 2625 | 0.0791          | 0.9730   |
  | 0.0005        | 35.02 | 2700 | 0.1285          | 0.9730   |
  | 0.0004        | 36.02 | 2775 | 0.1719          | 0.9730   |
  | 0.0007        | 37.02 | 2850 | 0.1799          | 0.9730   |
  | 0.0004        | 38.02 | 2925 | 0.1936          | 0.9730   |
  | 0.0004        | 39.02 | 3000 | 0.1844          | 0.9730   |
  | 0.0004        | 40.02 | 3075 | 0.1790          | 0.9730   |
  | 0.0004        | 41.02 | 3150 | 0.1747          | 0.9730   |
  | 0.0004        | 42.02 | 3225 | 0.1359          | 0.9730   |
  | 0.0004        | 43.02 | 3300 | 0.1283          | 0.9730   |
  | 0.0004        | 44.02 | 3375 | 0.1209          | 0.9730   |
  | 0.0004        | 45.02 | 3450 | 0.0876          | 0.9730   |
  | 0.0004        | 46.02 | 3525 | 0.0933          | 0.9730   |
  | 0.0004        | 47.02 | 3600 | 0.0976          | 0.9730   |
  | 0.0004        | 48.02 | 3675 | 0.1011          | 0.9730   |
  | 0.0004        | 49.02 | 3750 | 0.1050          | 0.9730   |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.8.0+cu111
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  