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VideoMAE Kinetics Wlasl 100 Signer 200ep CoR

This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.4810 Accuracy: 0.7071

Fontehuggingface.co/Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR/tree/bb393d659a16037de772b3d9d843546a01fb9106
TipoOtherModelo baseMCG-NJU/videomae-base-finetuned-kineticsVersãoRevision bb393d6Cnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
329 MB
Modelo base
MCG-NJU/videomae-base-finetuned-kinetics
Versão
vRevision bb393d6
Atualizado
24 de out. de 2026
Downloads
11
Fonte
Hugging Face

Descrição da fonte

videoMAE_kinetics_wlasl_100__signer_200ep_coR

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

  • Loss: 1.4810
  • Accuracy: 0.7071

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: 36000
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
18.5250.0051804.61330.0148
18.4261.00503604.58440.0355
18.08922.00505404.48540.0473
16.92673.00507214.20440.1095
15.40064.0059013.82100.2367
13.38735.005010813.46360.3402
11.39716.005012613.06290.4349
9.32437.005014422.72340.5148
7.4888.00516222.37140.5799
5.74299.005018022.03920.6450
4.270310.005019821.84130.6568
3.035111.005021631.60960.6627
2.119112.00523431.45380.6982
1.399713.005025231.36700.6627
0.955214.005027031.33830.6953
0.641815.005028841.21760.7189
0.47616.00530641.16030.7071
0.341317.005032441.17710.7041
0.252918.005034241.04120.7278
0.225519.005036051.24960.6746
0.167520.00537851.19290.7101
0.109321.005039651.19920.7041
0.113822.005041451.23770.7189
0.143223.005043261.22300.7071
0.086824.00545061.19350.7308
0.080325.005046861.22110.7160
0.131226.005048661.29530.6953
0.135627.005050471.42100.6746
0.133828.00552271.20000.7219
0.113229.005054071.36020.6953
0.126630.005055871.36820.6923
0.101931.005057681.20610.7189
0.11332.00559481.32690.7041
0.184633.005061281.36740.6893
0.133734.005063081.41510.7101
0.104535.005064891.29970.7249
0.141936.00566691.48810.6953
0.101537.005068491.45750.7012
0.098438.005070291.44810.6864
0.147839.005072101.89200.6598
0.221540.00573901.63550.6982
0.182741.005075701.63370.6805
0.075842.005077501.58140.6893
0.10943.005079311.52560.7012
0.053944.00581111.48100.7071

Framework versions

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

Fontes

1 fonte
Hugging FacePrimárioVersão bb393d659a16037de772b3d9d843546a01fb9106
huggingface.co/Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR/tree/bb393d659a16037de772b3d9d843546a01fb9106

Verificado 24 de out.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 329 MB · SHA-256 3e0004532c7a…d140 · Hugging Face

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Trechos de fonte

3 trechos
Readme6 de ago.huggingface.co/Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videoMAE_kinetics_wlasl_100__signer_200ep_coR 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_kinetics_wlasl_100__signer_200ep_coR This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.4810 - Accuracy: 0.7071 ## 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: 36000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 18.525 | 0.005 | 180 | 4.6133 | 0.0148 | | 18.426 | 1.0050 | 360 | 4.5844 | 0.0355 | | 18.0892 | 2.0050 | 540 | 4.4854 | 0.0473 | | 16.9267 | 3.0050 | 721 | 4.2044 | 0.1095 | | 15.4006 | 4.005 | 901 | 3.8210 | 0.2367 | | 13.3873 | 5.0050 | 1081 | 3.4636 | 0.3402 | | 11.3971 | 6.0050 | 1261 | 3.0629 | 0.4349 | | 9.3243 | 7.0050 | 1442 | 2.7234 | 0.5148 | | 7.488 | 8.005 | 1622 | 2.3714 | 0.5799 | | 5.7429 | 9.0050 | 1802 | 2.0392 | 0.6450 | | 4.2703 | 10.0050 | 1982 | 1.8413 | 0.6568 | | 3.0351 | 11.0050 | 2163 | 1.6096 | 0.6627 | | 2.1191 | 12.005 | 2343 | 1.4538 | 0.6982 | | 1.3997 | 13.0050 | 2523 | 1.3670 | 0.6627 | | 0.9552 | 14.0050 | 2703 | 1.3383 | 0.6953 | | 0.6418 | 15.0050 | 2884 | 1.2176 | 0.7189 | | 0.476 | 16.005 | 3064 | 1.1603 | 0.7071 | | 0.3413 | 17.0050 | 3244 | 1.1771 | 0.7041 | | 0.2529 | 18.0050 | 3424 | 1.0412 | 0.7...

Note24 de out.huggingface.co/Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR

Source context: 11 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR

Note6 de ago.huggingface.co/Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR

Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/videoMAE_kinetics_wlasl_100__signer_200ep_coR