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metadata
license: cc-by-nc-4.0
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: videomae-base-finetuned-sign-subset
    results: []

videomae-base-finetuned-sign-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: 3.3672
  • Accuracy: 0.1905

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
  • training_steps: 270
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.04 11 2.4220 0.0870
2.3491 1.04 22 2.6315 0.0
2.3491 2.04 33 2.6680 0.0435
2.2285 3.04 44 2.8487 0.1304
2.2285 4.04 55 3.0361 0.0870
1.996 5.04 66 3.0258 0.1304
1.996 6.04 77 3.2125 0.1304
1.6956 7.04 88 3.2063 0.1304
1.6956 8.04 99 3.1919 0.1304
1.5088 9.04 110 3.1940 0.1304
1.3777 10.04 121 3.3180 0.1739
1.3777 11.04 132 3.3112 0.1304
1.1509 12.04 143 3.3400 0.1304
1.1509 13.04 154 3.2550 0.1739
0.9036 14.04 165 3.3682 0.1304
0.9036 15.04 176 3.3775 0.1304
0.8303 16.04 187 3.4701 0.1304
0.8303 17.04 198 3.4340 0.1739
0.6683 18.04 209 3.4843 0.1304
0.5126 19.04 220 3.3552 0.2174
0.5126 20.04 231 3.3702 0.2609
0.3728 21.04 242 3.3871 0.2609
0.3728 22.04 253 3.3565 0.2609
0.3291 23.04 264 3.3861 0.3043
0.3291 24.02 270 3.3876 0.3043

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2