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

videomae-base-finetuned-ASBD_ESBD

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: 1.4178
  • Accuracy: 0.5714

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: 12
  • eval_batch_size: 12
  • 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: 500

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.504 0.02 11 1.3929 0.3433
1.3539 1.02 22 1.3380 0.1940
1.2957 2.02 33 1.3519 0.2239
1.2368 3.02 44 1.3220 0.3881
1.1561 4.02 55 1.2803 0.3134
1.0195 5.02 66 1.2588 0.5373
0.8594 6.02 77 1.1591 0.5075
0.8756 7.02 88 0.9532 0.6119
0.6488 8.02 99 1.1922 0.5373
0.4427 9.02 110 0.9780 0.6567
0.3975 10.02 121 1.3228 0.5373
0.3978 11.02 132 1.2083 0.6418
0.2859 12.02 143 1.0027 0.7463
0.3441 13.02 154 1.3718 0.5821
0.2239 14.02 165 1.4324 0.5821
0.2275 15.02 176 1.1823 0.6418
0.1734 16.02 187 1.5484 0.6119
0.2451 17.02 198 1.3764 0.5821
0.1317 18.02 209 1.3731 0.6716
0.0778 19.02 220 1.3567 0.7164
0.1963 20.02 231 1.0905 0.7164
0.1474 21.02 242 2.1361 0.4627
0.0487 22.02 253 1.2189 0.7164
0.0699 23.02 264 1.7618 0.5970
0.1576 24.02 275 1.1939 0.7463
0.0377 25.02 286 1.2287 0.7313
0.0674 26.02 297 1.5247 0.6567
0.0188 27.02 308 1.7585 0.6567
0.0681 28.02 319 1.7868 0.6567
0.0341 29.02 330 1.3745 0.6567
0.05 30.02 341 1.8781 0.6418
0.0269 31.02 352 1.9228 0.5970
0.0213 32.02 363 1.8014 0.6119
0.0061 33.02 374 1.4477 0.6866
0.0338 34.02 385 1.5303 0.6567
0.0086 35.02 396 1.5219 0.7015
0.0891 36.02 407 1.8414 0.5821
0.0032 37.02 418 1.8731 0.5821
0.0028 38.02 429 1.6881 0.6418
0.0434 39.02 440 1.7288 0.6567
0.0018 40.02 451 1.8235 0.6119
0.0232 41.02 462 1.8903 0.6119
0.0016 42.02 473 1.9292 0.6119
0.0016 43.02 484 1.9059 0.6119
0.0029 44.02 495 1.8093 0.6418
0.0519 45.01 500 1.8045 0.6418

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3