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metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-finetuned-ucf101-subset
    results: []

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:

  • Loss: 3.0235
  • Accuracy: 0.2575

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 480

Training results

Training Loss Epoch Step Validation Loss Accuracy
4.2682 0.0646 31 4.2493 0.0033
4.2584 1.0646 62 4.2434 0.0134
4.2518 2.0646 93 4.2246 0.0167
4.2445 3.0646 124 4.2208 0.0067
4.2272 4.0646 155 4.2230 0.0100
4.205 5.0646 186 4.2111 0.0234
4.1238 6.0646 217 4.1112 0.0368
3.9136 7.0646 248 3.8530 0.0736
3.6241 8.0646 279 3.6734 0.1171
3.3103 9.0646 310 3.5261 0.1070
3.0981 10.0646 341 3.3860 0.1639
2.8216 11.0646 372 3.1791 0.2140
2.6108 12.0646 403 3.1618 0.2441
2.598 13.0646 434 3.0793 0.2341
2.5023 14.0646 465 3.0194 0.2575
2.513 15.0312 480 3.0668 0.2375

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu118
  • Datasets 3.2.0
  • Tokenizers 0.21.0