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Videomae Base Finetuned Kinetics 0403 Final Only5sec

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: 0.9866 Accuracy: 0.7954

Sourcehuggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec/tree/33034828d5d45edb41b17338f9dd6c0b0d057f7a
KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 3303482

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 3303482
Updated
Sep 18, 2026
Downloads
3
Source
Hugging Face

Source description

videomae-base-finetuned-kinetics-0403_final_only5sec

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: 0.9866
  • Accuracy: 0.7954

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: 62100

Training results

Training LossEpochStepValidation LossAccuracy
0.02580.01006220.34080.8950
0.01481.010012440.35550.8603
0.00132.010018660.52790.8754
0.00443.010024880.80370.8283
0.01274.010031100.63750.8461
1.00485.010037321.24570.7811
0.00066.010043540.75760.8292
0.00037.010049760.47660.8968
0.00278.010055980.61470.8496
0.00129.010062200.62140.8345
0.015710.010068420.69980.8514
0.009911.010074641.19070.7847
0.053712.010080861.29550.8043
0.000113.010087081.12350.7972
0.000714.010093301.31380.7900
0.002815.010099521.03100.8221
0.000816.0100105740.81990.8514
0.01517.0100111960.57740.8852
0.000218.0100118180.99530.8407
0.646319.0100124401.27040.8132
0.000120.0100130621.02140.8203
0.001221.0100136841.23720.8194
0.000122.0100143061.09670.8372

Framework versions

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

Sources

1 source
Hugging FacePrimaryVersion 33034828d5d45edb41b17338f9dd6c0b0d057f7a
huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec/tree/33034828d5d45edb41b17338f9dd6c0b0d057f7a

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 4c5879707404…62a0 · Hugging Face

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Source excerpts

2 excerpts
ReadmeSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec

--- 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-0403_final_only5sec 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-0403_final_only5sec 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: 0.9866 - Accuracy: 0.7954 ## 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: 62100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 0.0258 | 0.0100 | 622 | 0.3408 | 0.8950 | | 0.0148 | 1.0100 | 1244 | 0.3555 | 0.8603 | | 0.0013 | 2.0100 | 1866 | 0.5279 | 0.8754 | | 0.0044 | 3.0100 | 2488 | 0.8037 | 0.8283 | | 0.0127 | 4.0100 | 3110 | 0.6375 | 0.8461 | | 1.0048 | 5.0100 | 3732 | 1.2457 | 0.7811 | | 0.0006 | 6.0100 | 4354 | 0.7576 | 0.8292 | | 0.0003 | 7.0100 | 4976 | 0.4766 | 0.8968 | | 0.0027 | 8.0100 | 5598 | 0.6147 | 0.8496 | | 0.0012 | 9.0100 | 6220 | 0.6214 | 0.8345 | | 0.0157 | 10.0100 | 6842 | 0.6998 | 0.8514 | | 0.0099 | 11.0100 | 7464 | 1.1907 | 0.7847 | | 0.0537 | 12.0100 | 8086 | 1.2955 | 0.8043 | | 0.0001 | 13.0100 | 8708 | 1.1235 | 0.7972 | | 0.0007 | 14.0100 | 9330 | 1.3138 | 0.7900 | | 0.0028 | 15.0100 | 9952 | 1.0310 | 0.8221 | | 0.0008 | 16.0100 | 10574 | 0.8199 | 0.8514 | | 0.015 | 17.0100 | 11196 | 0.5774 | 0.8852 | | 0.0002 | 18.0100 | 11818 | 0.9953 | 0.8407 | | 0.6463 | 19.0100 | 12440 | 1.2704 | 0.8132 | | 0.0001 | 20.0100 | 13...

NoteSep 18huggingface.co/d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec

Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec