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Videomae Base Finetuned Kinetics 0326 Final Patience

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: 0.6152 Accuracy: 0.8422

KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision a8bcbd9

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision a8bcbd9
Updated
Sep 18, 2026
Downloads
15
Source
Hugging Face

Source description

videomae-base-finetuned-kinetics-0326_final_patience

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: 0.6152
  • Accuracy: 0.8422

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
0.00320.016870.84300.8112
0.00671.0113740.82570.7844
0.01932.0120610.36680.8720
0.17673.0127480.77600.7966
1.12294.0134350.76410.8079
0.01235.0141220.36140.8825
0.02996.0148091.00450.7593
0.317.0154960.89820.8290
0.00798.0161830.69620.8525
0.26239.0168701.73030.6807
0.407610.0175570.92150.7998
0.104911.0182441.05850.7966
0.007912.0189311.04300.8039
0.036613.0196180.63440.8590
0.000714.01103050.86990.8379
0.275615.01109920.92750.8217

Framework versions

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

Sources

1 source
Hugging FacePrimaryVersion a8bcbd9ecde8326abe5a0b03b367feb9b0c64053
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0326_final_patience/tree/a8bcbd9ecde8326abe5a0b03b367feb9b0c64053

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 bebef719f530…4cc3 · Hugging Face

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Source excerpts

2 excerpts

--- 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_patience 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_patience 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: 0.6152 - Accuracy: 0.8422 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.0032 | 0.01 | 687 | 0.8430 | 0.8112 | | 0.0067 | 1.01 | 1374 | 0.8257 | 0.7844 | | 0.0193 | 2.01 | 2061 | 0.3668 | 0.8720 | | 0.1767 | 3.01 | 2748 | 0.7760 | 0.7966 | | 1.1229 | 4.01 | 3435 | 0.7641 | 0.8079 | | 0.0123 | 5.01 | 4122 | 0.3614 | 0.8825 | | 0.0299 | 6.01 | 4809 | 1.0045 | 0.7593 | | 0.31 | 7.01 | 5496 | 0.8982 | 0.8290 | | 0.0079 | 8.01 | 6183 | 0.6962 | 0.8525 | | 0.2623 | 9.01 | 6870 | 1.7303 | 0.6807 | | 0.4076 | 10.01 | 7557 | 0.9215 | 0.7998 | | 0.1049 | 11.01 | 8244 | 1.0585 | 0.7966 | | 0.0079 | 12.01 | 8931 | 1.0430 | 0.8039 | | 0.0366 | 13.01 | 9618 | 0.6344 | 0.8590 | | 0.0007 | 14.01 | 10305 | 0.8699 | 0.8379 | | 0.2756 | 15.01 | 10992 | 0.9275 | 0.8217 | ### Framework versions - Transformers 4.48.0 - Pytorch 2.5.1+cu124 - Datasets 3.2.0 - Tokenizers 0.21.0

Source context: 15 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0326_final_patience