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