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Videomae Base Finetuned Kinetics 0326 Final Imgsz256

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: 1.0012 Accuracy: 0.6828

Sourcehuggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0326_final_imgsz256/tree/b2d9de57faf7ecd36a432875fa8dd125df4b1c41
KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision b2d9de5

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision b2d9de5
Updated
Sep 18, 2026
Downloads
4
Source
Hugging Face

Source description

videomae-base-finetuned-kinetics-0326_final_imgsz256

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: 1.0012
  • Accuracy: 0.6828

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: 68700

Training results

Training LossEpochStepValidation LossAccuracy
0.26690.016870.73240.7318
0.3111.0113741.28550.6386
0.16272.0120610.72970.7788
0.46733.0127481.75320.6191
0.96944.0134350.93050.7715
0.23725.0141221.00850.7423
0.36086.0148090.74860.7618
0.83747.0154961.11760.7366
0.04458.0161831.21310.7382
0.67959.0168701.75160.6345
0.223410.0175572.25030.5989
0.030611.0182441.52130.7115
0.139612.0189311.30850.7253

Framework versions

  • Transformers 4.48.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0

Sources

1 source
Hugging FacePrimaryVersion b2d9de57faf7ecd36a432875fa8dd125df4b1c41
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0326_final_imgsz256/tree/b2d9de57faf7ecd36a432875fa8dd125df4b1c41

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 7d9163275d02…6fbd · Hugging Face

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Source excerpts

2 excerpts
ReadmeSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0326_final_imgsz256

--- 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-0326_final_imgsz256 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-0326_final_imgsz256 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: 1.0012 - Accuracy: 0.6828 ## 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: 68700 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.2669 | 0.01 | 687 | 0.7324 | 0.7318 | | 0.311 | 1.01 | 1374 | 1.2855 | 0.6386 | | 0.1627 | 2.01 | 2061 | 0.7297 | 0.7788 | | 0.4673 | 3.01 | 2748 | 1.7532 | 0.6191 | | 0.9694 | 4.01 | 3435 | 0.9305 | 0.7715 | | 0.2372 | 5.01 | 4122 | 1.0085 | 0.7423 | | 0.3608 | 6.01 | 4809 | 0.7486 | 0.7618 | | 0.8374 | 7.01 | 5496 | 1.1176 | 0.7366 | | 0.0445 | 8.01 | 6183 | 1.2131 | 0.7382 | | 0.6795 | 9.01 | 6870 | 1.7516 | 0.6345 | | 0.2234 | 10.01 | 7557 | 2.2503 | 0.5989 | | 0.0306 | 11.01 | 8244 | 1.5213 | 0.7115 | | 0.1396 | 12.01 | 8931 | 1.3085 | 0.7253 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0

NoteSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0326_final_imgsz256

Source context: 4 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0326_final_imgsz256