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Videomae Base Finetuned Signlanguage

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.3358 Accuracy: 0.6567

Sourcehuggingface.co/ihsanahakiim/videomae-base-finetuned-signlanguage/tree/5285538ab43cf59c125022ade93746c76421b2be
KindOtherBase modelMCG-NJU/videomae-baseVersionRevision 5285538

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base
Version
vRevision 5285538
Updated
Sep 18, 2026
Downloads
9
Source
Hugging Face

Source description

videomae-base-finetuned-signlanguage

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

  • Loss: 1.3358
  • Accuracy: 0.6567

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: 1e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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: 0.1
  • training_steps: 3560

Training results

Training LossEpochStepValidation LossAccuracy
4.23720.0065234.24390.0186
4.23251.0065464.23690.0186
4.17952.0065694.22500.0233
4.2113.0065924.21410.0140
4.23614.00651154.20510.0372
4.25245.00651384.20520.0233
4.22976.00651614.20140.0186
4.25967.00651844.19500.0233
4.19118.00652074.18980.0326
4.1849.00652304.18600.0279
4.173110.00652534.16800.0419
4.09811.00652764.14130.0512
4.110512.00652994.13510.0279
4.147713.00653224.11820.0372
4.012114.00653454.03240.0605
3.858715.00653683.99730.0512
3.887816.00653913.90770.0651
3.720517.00654143.89010.0698
3.661318.00654373.73470.1349
3.543819.00654603.62750.1488
3.403320.00654833.54950.1442
3.204321.00655063.58640.1349
3.147722.00655293.45150.1674
3.034423.00655523.31100.2233
2.945924.00655753.26450.2605
2.662925.00655983.17460.2558
2.76426.00656213.08330.3163
2.492427.00656442.99180.3023
2.669628.00656673.00090.3349
2.461629.00656902.83960.4
2.208430.00657132.80390.3674
2.301131.00657362.74650.4
2.105932.00657592.68650.4140
2.052533.00657822.60700.4326
2.105434.00658052.63870.3953
1.879135.00658282.55390.4326
1.783436.00658512.47500.4326
1.574937.00658742.48800.4233
1.616238.00658972.35810.4884
1.561139.00659202.28460.5256
1.544940.00659432.29990.5116
1.601341.00659662.23490.5302
1.395942.00659892.19570.5488
1.160743.006510122.15590.5209
1.266344.006510352.11920.5721
1.086945.006510582.05220.5535
1.247746.006510812.05970.5767
0.966547.006511042.03650.5535
1.052148.006511271.96690.5767
0.827349.006511501.99180.5907
0.839650.006511731.95760.5860
0.954351.006511961.93710.5953
0.809552.006512191.88000.5953
0.769453.006512421.87370.6
0.824354.006512651.88460.6093
0.663255.006512881.82300.6
0.744656.006513111.78980.6093
0.704457.006513341.77400.5907
0.673258.006513571.80610.6047
0.578659.006513801.70600.6186
0.634860.006514031.70040.6140
0.570661.006514261.70130.6279
0.500762.006514491.69920.6186
0.507863.006514721.66490.6047
0.504864.006514951.64490.6140
0.452665.006515181.62560.6279
0.50466.006515411.64010.6372
0.382467.006515641.59410.6093
0.45368.006515871.62360.6186
0.361869.006516101.61000.6186
0.368970.006516331.54880.6419
0.354571.006516561.53900.6465
0.412672.006516791.52870.6558
0.273473.006517021.49780.6465
0.314474.006517251.50380.6326
0.315275.006517481.56920.6326
0.37176.006517711.53310.6558
0.303377.006517941.47330.6465
0.257478.006518171.56940.5907
0.256279.006518401.50970.6279
0.216280.006518631.47820.6512
0.249381.006518861.43500.6465
0.217382.006519091.47300.6093
0.250883.006519321.47350.6186
0.193284.006519551.44910.6326
0.182285.006519781.41550.6326
0.205186.006520011.44310.6419
0.226987.006520241.40290.6419
0.174788.006520471.46430.6233
0.146489.006520701.39210.6558
0.164290.006520931.40330.6512
0.158291.006521161.37280.6512
0.164192.006521391.37560.6326
0.129293.006521621.37310.6512
0.128594.006521851.35590.6698
0.140595.006522081.41260.6233
0.129996.006522311.35240.6419
0.116697.006522541.38120.6512
0.143498.006522771.40550.6279
0.174899.006523001.38940.6558
0.0999100.006523231.36650.6326
0.1361101.006523461.37760.6372
0.118102.006523691.36350.6558
0.0996103.006523921.34770.6512
0.1232104.006524151.35500.6419
0.0783105.006524381.34600.6233
0.1517106.006524611.35270.6279
0.1007107.006524841.30400.6465
0.1036108.006525071.32160.6698
0.1085109.006525301.29750.6326
0.0691110.006525531.34010.6512
0.1231111.006525761.32510.6372
0.0801112.006525991.31200.6605
0.0784113.006526221.30610.6605
0.0891114.006526451.28820.6558
0.0792115.006526681.35310.6558
0.0772116.006526911.32000.6698
0.1068117.006527141.31860.6744
0.0711118.006527371.30670.6419
0.0982119.006527601.31610.6512
0.0741120.006527831.30290.6512
0.1507121.006528061.34060.6605
0.0602122.006528291.31870.6558
0.0748123.006528521.28740.6605
0.0638124.006528751.28710.6791
0.0915125.006528981.28690.6465
0.0749126.006529211.28590.6558
0.0717127.006529441.32220.6372
0.0539128.006529671.32630.6326
0.0488129.006529901.29450.6512
0.0696130.006530131.26360.6698
0.0665131.006530361.29100.6698
0.0562132.006530591.28200.6558
0.0527133.006530821.29270.6651
0.057134.006531051.28460.6558
0.0764135.006531281.31040.6651
0.0805136.006531511.31100.6465
0.0503137.006531741.31070.6558
0.0629138.006531971.29150.6465
0.0491139.006532201.27530.6558
0.0456140.006532431.31050.6605
0.053141.006532661.26860.6558
0.051142.006532891.28310.6651
0.0669143.006533121.28520.6698
0.0445144.006533351.28680.6651
0.0414145.006533581.28060.6698
0.0575146.006533811.28150.6651
0.0392147.006534041.25960.6558
0.0898148.006534271.26660.6698
0.0617149.006534501.26290.6605
0.0453150.006534731.27970.6651
0.0398151.006534961.26980.6558
0.0435152.006535191.27210.6558
0.0507153.006535421.27450.6512
0.0525154.005135601.27770.6512

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.0.1+cu118
  • Datasets 3.3.2
  • Tokenizers 0.21.0

Sources

1 source
Hugging FacePrimaryVersion 5285538ab43cf59c125022ade93746c76421b2be
huggingface.co/ihsanahakiim/videomae-base-finetuned-signlanguage/tree/5285538ab43cf59c125022ade93746c76421b2be

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 c187c030f15e…d95a · Hugging Face

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Source excerpts

2 excerpts
ReadmeSep 18huggingface.co/ihsanahakiim/videomae-base-finetuned-signlanguage

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-signlanguage 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-signlanguage This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3358 - Accuracy: 0.6567 ## 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: 1e-05 - train_batch_size: 32 - eval_batch_size: 32 - 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: 0.1 - training_steps: 3560 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:--------:|:----:|:---------------:|:--------:| | 4.2372 | 0.0065 | 23 | 4.2439 | 0.0186 | | 4.2325 | 1.0065 | 46 | 4.2369 | 0.0186 | | 4.1795 | 2.0065 | 69 | 4.2250 | 0.0233 | | 4.211 | 3.0065 | 92 | 4.2141 | 0.0140 | | 4.2361 | 4.0065 | 115 | 4.2051 | 0.0372 | | 4.2524 | 5.0065 | 138 | 4.2052 | 0.0233 | | 4.2297 | 6.0065 | 161 | 4.2014 | 0.0186 | | 4.2596 | 7.0065 | 184 | 4.1950 | 0.0233 | | 4.1911 | 8.0065 | 207 | 4.1898 | 0.0326 | | 4.184 | 9.0065 | 230 | 4.1860 | 0.0279 | | 4.1731 | 10.0065 | 253 | 4.1680 | 0.0419 | | 4.098 | 11.0065 | 276 | 4.1413 | 0.0512 | | 4.1105 | 12.0065 | 299 | 4.1351 | 0.0279 | | 4.1477 | 13.0065 | 322 | 4.1182 | 0.0372 | | 4.0121 | 14.0065 | 345 | 4.0324 | 0.0605 | | 3.8587 | 15.0065 | 368 | 3.9973 | 0.0512 | | 3.8878 | 16.0065 | 391 | 3.9077 | 0.0651 | | 3.7205 | 17.0065 | 414 | 3.8901 | 0.0698 | | 3.6613 | 18.0065 | 437 | 3.7347 | 0.1349 | | 3.5438 | 19.0065 | 460 | 3.6275 | 0.1488 | | 3.4033 | 20.0065 | 483 | 3.5495 | 0.1442 | | 3.2043 | 21.0065 | 506 | 3.5864 | 0.1349 | | 3.1477 | 22.0065 | 529 | 3.4515 | 0.1674 | | 3.03...

NoteSep 18huggingface.co/ihsanahakiim/videomae-base-finetuned-signlanguage

Source context: 9 downloads · 1 likes · Pipeline video-classification · Library transformers · Repo ihsanahakiim/videomae-base-finetuned-signlanguage