Hugging Face's logo

beingbatman
/
MAE-CT-CPC-Dicotomized-n0-m1-d1-v9

Video Classification
Transformers
Safetensors
videomae
Generated from Trainer
Inference Endpoints
Model card Files Community
MAE-CT-CPC-Dicotomized-n0-m1-d1-v9 / README.md
beingbatman's picture
beingbatman
Model save
a235b68 verified
preview code
|
raw
history blame contribute delete
4.61 kB
metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large-finetuned-kinetics
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: MAE-CT-CPC-Dicotomized-n0-m1-d1-v9
    results: []

MAE-CT-CPC-Dicotomized-n0-m1-d1-v9

This model is a fine-tuned version of MCG-NJU/videomae-large-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6419
  • Accuracy: 0.5

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: 1e-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: 2400

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6819 0.0204 49 0.6641 0.5789
0.6201 1.0204 98 0.6368 0.5789
0.6787 2.0204 147 0.6109 0.5789
0.6484 3.0204 196 0.6305 0.6316
0.6357 4.0204 245 0.6794 0.5263
0.5692 5.0204 294 0.6938 0.5263
0.658 6.0204 343 0.6696 0.5789
0.5112 7.0204 392 0.5669 0.6316
0.3719 8.0204 441 0.8023 0.6316
0.4573 9.0204 490 0.5991 0.6316
0.2915 10.0204 539 0.7899 0.6842
0.3723 11.0204 588 0.9848 0.5263
0.1372 12.0204 637 0.9510 0.6316
0.0066 13.0204 686 1.1872 0.5789
0.2218 14.0204 735 1.1692 0.7368
0.7666 15.0204 784 1.1125 0.6842
0.2171 16.0204 833 1.2615 0.7368
0.1152 17.0204 882 1.3683 0.7368
0.1941 18.0204 931 1.3915 0.7368
0.0233 19.0204 980 1.5972 0.5789
0.2367 20.0204 1029 1.7445 0.6842
0.1575 21.0204 1078 2.4036 0.6316
0.0008 22.0204 1127 2.2633 0.6316
0.019 23.0204 1176 2.2078 0.6842
0.0006 24.0204 1225 2.1281 0.6316
0.0004 25.0204 1274 2.0100 0.7368
0.0002 26.0204 1323 2.3862 0.6316
0.0003 27.0204 1372 2.1579 0.6842
0.0372 28.0204 1421 2.1226 0.6842
0.1547 29.0204 1470 2.4949 0.6842
0.0015 30.0204 1519 1.8815 0.6842
0.0005 31.0204 1568 2.2582 0.6316
0.0002 32.0204 1617 2.1774 0.6316
0.0001 33.0204 1666 2.2222 0.6316
0.0001 34.0204 1715 2.3560 0.6316
0.0001 35.0204 1764 2.3904 0.6316
0.0001 36.0204 1813 2.2240 0.7368
0.0002 37.0204 1862 2.2880 0.6842
0.0002 38.0204 1911 2.3010 0.6842
0.0001 39.0204 1960 2.3124 0.6842
0.0001 40.0204 2009 2.2903 0.6842
0.1744 41.0204 2058 2.3067 0.6842
0.0001 42.0204 2107 2.3422 0.6842
0.0001 43.0204 2156 2.3477 0.6842
0.0001 44.0204 2205 2.3783 0.6316
0.0001 45.0204 2254 2.3447 0.6842
0.0001 46.0204 2303 2.3415 0.6842
0.0001 47.0204 2352 2.3419 0.6842
0.0001 48.02 2400 2.3470 0.6842

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.0.1+cu117
  • Datasets 3.0.1
  • Tokenizers 0.20.0