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VideoMAE Base Wlasl 100 50ep CoR P10

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: 2.5394 Accuracy: 0.4911

Sourcehuggingface.co/Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10/tree/248d856b52048c5796cb3b2bf96fe6b539ec8677
KindOtherBase modelMCG-NJU/videomae-baseVersionRevision 248d856Bgrade

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base
Version
vRevision 248d856
Updated
Oct 24, 2026
Downloads
3
Source
Hugging Face

Source description

videoMAE_base_wlasl_100_50ep_coR_p10

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: 2.5394
  • Accuracy: 0.4911

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: 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: 9000
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
18.64840.021804.64340.0089
18.58631.02003604.62570.0178
18.51412.01995404.60940.0237
18.39513.02007214.61050.0207
18.45984.029014.60590.0148
18.32575.020010814.56100.0266
17.93776.019912614.45750.0325
17.08097.020014424.31420.0355
16.43498.0216224.21450.0296
15.80979.020018023.99670.0592
14.693710.019919823.90200.0917
13.328111.020021633.69370.1036
12.002812.0223433.40950.1834
10.454513.020025233.11940.2574
8.931714.019927033.01320.2604
7.357515.020028842.85620.2959
6.043716.0230642.69420.3373
4.881817.020032442.58830.3550
3.813518.019934242.53860.3609
2.793619.020036052.43620.4053
2.105920.0237852.49490.4260
1.530921.020039652.37700.3935
1.091122.019941452.31480.4467
0.839523.020043262.39400.4231
0.652524.0245062.29070.4675
0.431325.020046862.22530.4615
0.326226.019948662.27760.4852
0.209727.020050472.41510.4556
0.181528.0252272.37680.4793
0.112429.020054072.43080.4852
0.116530.019955872.44290.5
0.091531.020057682.46440.4822
0.082232.0259482.51560.4911
0.055533.020061282.60180.4941
0.069334.019963082.58390.4822
0.060935.020064892.65240.4882
0.071936.0266692.62800.4793
0.06737.020068492.71130.4675
0.059238.019970292.59070.4822
0.062139.020072102.63480.4793
0.079140.0273902.53940.4911

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.1

Sources

1 source
Hugging FacePrimaryVersion 248d856b52048c5796cb3b2bf96fe6b539ec8677
huggingface.co/Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10/tree/248d856b52048c5796cb3b2bf96fe6b539ec8677

Verified Oct 24

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 773cf760e15f…c697 · Hugging Face

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Source excerpts

3 excerpts
ReadmeAug 6huggingface.co/Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10

--- 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_wlasl_100_50ep_coR_p10 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # videoMAE_base_wlasl_100_50ep_coR_p10 This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.5394 - Accuracy: 0.4911 ## 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: 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: 9000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 18.6484 | 0.02 | 180 | 4.6434 | 0.0089 | | 18.5863 | 1.0200 | 360 | 4.6257 | 0.0178 | | 18.5141 | 2.0199 | 540 | 4.6094 | 0.0237 | | 18.3951 | 3.0200 | 721 | 4.6105 | 0.0207 | | 18.4598 | 4.02 | 901 | 4.6059 | 0.0148 | | 18.3257 | 5.0200 | 1081 | 4.5610 | 0.0266 | | 17.9377 | 6.0199 | 1261 | 4.4575 | 0.0325 | | 17.0809 | 7.0200 | 1442 | 4.3142 | 0.0355 | | 16.4349 | 8.02 | 1622 | 4.2145 | 0.0296 | | 15.8097 | 9.0200 | 1802 | 3.9967 | 0.0592 | | 14.6937 | 10.0199 | 1982 | 3.9020 | 0.0917 | | 13.3281 | 11.0200 | 2163 | 3.6937 | 0.1036 | | 12.0028 | 12.02 | 2343 | 3.4095 | 0.1834 | | 10.4545 | 13.0200 | 2523 | 3.1194 | 0.2574 | | 8.9317 | 14.0199 | 2703 | 3.0132 | 0.2604 | | 7.3575 | 15.0200 | 2884 | 2.8562 | 0.2959 | | 6.0437 | 16.02 | 3064 | 2.6942 | 0.3373 | | 4.8818 | 17.0200 | 3244 | 2.5883 | 0.3550 | | 3.8135 | 18.0199 | 3424 | 2.5386 | 0.3609 | | 2.7936 | 19.0200 | 3605 | 2.4362 | 0.4053 | | 2.1059 | 20.02 |...

NoteOct 24huggingface.co/Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10

Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10

NoteAug 6huggingface.co/Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10

Source context: 5 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/videoMAE_base_wlasl_100_50ep_coR_p10