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Videomae Base Finetuned Signlanguage 3

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: 1.5381 Accuracy: 0.6667

KindOtherBase modelMCG-NJU/videomae-baseVersionRevision 098191f

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base
Version
vRevision 098191f
Updated
Sep 18, 2026
Downloads
3
Source
Hugging Face

Source description

videomae-base-finetuned-signlanguage-3

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: 1.5381
  • Accuracy: 0.6667

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: 7200

Training results

Training LossEpochStepValidation LossAccuracy
4.28660.0043314.25920.0134
4.28061.0043624.24500.0134
4.24272.0043934.22920.0134
4.22793.00431244.22250.0268
4.21654.00431554.21760.0201
4.2255.00431864.21260.0268
4.20796.00432174.20610.0134
4.20437.00432484.20390.0134
4.19458.00432794.19830.0201
4.19469.00433104.19620.0134
4.177710.00433414.19230.0268
4.194111.00433724.18240.0268
4.150912.00434034.16030.0201
4.130813.00434344.12670.0336
4.046214.00434654.09010.0336
4.038915.00434964.05160.0537
3.985116.00435274.00590.0604
3.938417.00435583.97350.0604
3.840618.00435893.92600.0671
3.822319.00436203.80810.1007
3.722320.00436513.83930.1275
3.569221.00436823.66830.0872
3.471622.00437133.67820.1544
3.326723.00437443.47830.1409
3.124524.00437753.27970.2349
2.920725.00438063.21650.2282
2.82426.00438373.07330.3221
2.656227.00438683.05720.2282
2.545428.00438992.85090.4094
2.350329.00439302.75830.3691
2.316830.00439612.69290.4228
2.167731.00439922.57520.4631
1.925232.004310232.51220.4430
1.961833.004310542.41680.5101
1.835534.004310852.38450.4966
1.611635.004311162.36300.5034
1.454836.004311472.25360.4765
1.454837.004311782.18170.5168
1.344138.004312092.19020.5101
1.202939.004312402.14190.4966
1.291840.004312712.02490.5638
1.169341.004313022.04130.5436
1.132742.004313331.99670.5705
1.005543.004313641.95040.5705
0.925844.004313951.89760.5705
0.911545.004314261.84330.6107
0.819446.004314571.93840.5638
0.849247.004314881.83810.5638
0.750348.004315191.87640.5570
0.61249.004315501.83640.5235
0.520250.004315811.79600.5570
0.606951.004316121.83080.5570
0.490752.004316431.67180.6174
0.53753.004316741.75950.5705
0.472354.004317051.70040.5772
0.440255.004317361.73470.5570
0.348856.004317671.73990.6040
0.299657.004317981.60060.6040
0.329858.004318291.61100.5906
0.30159.004318601.67970.5638
0.256160.004318911.65860.5772

Framework versions

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

Sources

1 source
Hugging FacePrimaryVersion 098191faa95ff75b055856c4afa705005602c4de
huggingface.co/ihsanahakiim/videomae-base-finetuned-signlanguage-3/tree/098191faa95ff75b055856c4afa705005602c4de

Verified Sep 18

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 4f910f514a91…9de1 · 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 tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-signlanguage-3 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-3 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: 1.5381 - Accuracy: 0.6667 ## 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: 7200 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 4.2866 | 0.0043 | 31 | 4.2592 | 0.0134 | | 4.2806 | 1.0043 | 62 | 4.2450 | 0.0134 | | 4.2427 | 2.0043 | 93 | 4.2292 | 0.0134 | | 4.2279 | 3.0043 | 124 | 4.2225 | 0.0268 | | 4.2165 | 4.0043 | 155 | 4.2176 | 0.0201 | | 4.225 | 5.0043 | 186 | 4.2126 | 0.0268 | | 4.2079 | 6.0043 | 217 | 4.2061 | 0.0134 | | 4.2043 | 7.0043 | 248 | 4.2039 | 0.0134 | | 4.1945 | 8.0043 | 279 | 4.1983 | 0.0201 | | 4.1946 | 9.0043 | 310 | 4.1962 | 0.0134 | | 4.1777 | 10.0043 | 341 | 4.1923 | 0.0268 | | 4.1941 | 11.0043 | 372 | 4.1824 | 0.0268 | | 4.1509 | 12.0043 | 403 | 4.1603 | 0.0201 | | 4.1308 | 13.0043 | 434 | 4.1267 | 0.0336 | | 4.0462 | 14.0043 | 465 | 4.0901 | 0.0336 | | 4.0389 | 15.0043 | 496 | 4.0516 | 0.0537 | | 3.9851 | 16.0043 | 527 | 4.0059 | 0.0604 | | 3.9384 | 17.0043 | 558 | 3.9735 | 0.0604 | | 3.8406 | 18.0043 | 589 | 3.9260 | 0.0671 | | 3.8223 | 19.0043 | 620 | 3.8081 | 0.1007 | | 3.7223 | 20.0043 | 651 | 3.8393 | 0.1275 | | 3.5692 | 21.0043 | 682 | 3.6683 | 0.0872 | | 3.4716 | 22.0043 | 713 | 3.6782 | 0.1544 |...

Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo ihsanahakiim/videomae-base-finetuned-signlanguage-3