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Videomae Base Finetuned Kinetics Allkisa Crop Background 0228

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: 0.3129 Accuracy: 0.9163

Sourcehuggingface.co/d2o2ji/videomae-base-finetuned-kinetics-allkisa-crop-background-0228/tree/2ca4dbb1fc46b326467222a479ace3e412f18019
KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 2ca4dbb

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 2ca4dbb
Updated
Sep 18, 2026
Downloads
6
Source
Hugging Face

Source description

videomae-base-finetuned-kinetics-allkisa-crop-background-0228

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: 0.3129
  • Accuracy: 0.9163

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: 8
  • eval_batch_size: 8
  • seed: 42
  • 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: 0.05
  • training_steps: 10560

Training results

Training LossEpochStepValidation LossAccuracy
0.00350.02512650.70570.7302
0.00471.02515300.63690.7840
0.36252.02517951.07770.7099
0.0173.025110601.14920.6145
0.00014.025113250.59460.8394
0.00065.025115900.47630.8134
0.00366.025118550.47980.8093
0.02867.025121200.64860.8191
0.00038.025123850.84640.7775
0.00019.025126500.68910.8174
0.000310.025129150.52980.8582
0.000311.025131800.78320.8289
0.012.025134450.74450.8215
0.013.025137100.65940.8419
0.014.025139750.70890.8297
0.000115.025142400.65420.8509
0.016.025145050.76770.8346
0.017.025147700.82550.8183
0.001118.025150350.72380.8378
0.000119.025153000.78260.8329
0.000120.025155650.79800.8329

Framework versions

  • Transformers 4.48.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Sources

1 source
Hugging FacePrimaryVersion 2ca4dbb1fc46b326467222a479ace3e412f18019
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-allkisa-crop-background-0228/tree/2ca4dbb1fc46b326467222a479ace3e412f18019

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 03e8fbc456aa…cb8d · Hugging Face

Download file

Source excerpts

2 excerpts
ReadmeSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-allkisa-crop-background-0228

--- 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-base-finetuned-kinetics-allkisa-crop-background-0228 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-finetuned-kinetics-allkisa-crop-background-0228 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: 0.3129 - Accuracy: 0.9163 ## 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: 8 - eval_batch_size: 8 - seed: 42 - 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: 0.05 - training_steps: 10560 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.0035 | 0.0251 | 265 | 0.7057 | 0.7302 | | 0.0047 | 1.0251 | 530 | 0.6369 | 0.7840 | | 0.3625 | 2.0251 | 795 | 1.0777 | 0.7099 | | 0.017 | 3.0251 | 1060 | 1.1492 | 0.6145 | | 0.0001 | 4.0251 | 1325 | 0.5946 | 0.8394 | | 0.0006 | 5.0251 | 1590 | 0.4763 | 0.8134 | | 0.0036 | 6.0251 | 1855 | 0.4798 | 0.8093 | | 0.0286 | 7.0251 | 2120 | 0.6486 | 0.8191 | | 0.0003 | 8.0251 | 2385 | 0.8464 | 0.7775 | | 0.0001 | 9.0251 | 2650 | 0.6891 | 0.8174 | | 0.0003 | 10.0251 | 2915 | 0.5298 | 0.8582 | | 0.0003 | 11.0251 | 3180 | 0.7832 | 0.8289 | | 0.0 | 12.0251 | 3445 | 0.7445 | 0.8215 | | 0.0 | 13.0251 | 3710 | 0.6594 | 0.8419 | | 0.0 | 14.0251 | 3975 | 0.7089 | 0.8297 | | 0.0001 | 15.0251 | 4240 | 0.6542 | 0.8509 | | 0.0 | 16.0251 | 4505 | 0.7677 | 0.8346 | | 0.0 | 17.0251 | 4770 | 0.8255 | 0.8183 | | 0.0011 | 18.0251 | 5035 | 0.7238 | 0.8378 | | 0.0001 | 19.0251 | 5300 | 0.7826 | 0.8329 | | 0.0001 | 20.0251 | 5565 |...

NoteSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-allkisa-crop-background-0228

Source context: 6 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-allkisa-crop-background-0228