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RALL RGBCROP Aug16F 2DO2

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: 0.3981 Accuracy: 0.8173

ArtOtherBasismodellMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 4c3ec17

Modellquelle

Art
Other
Dateigröße
329 MB
Basismodell
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 4c3ec17
Aktualisiert
17. Sept. 2026
Downloads
5
Quelle
Hugging Face

Quellenbeschreibung

RALL_RGBCROP_Aug16F-2DO2

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: 0.3981
  • Accuracy: 0.8173

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.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: 3462

Training results

Training LossEpochStepValidation LossAccuracy
0.53510.08352890.60500.7444
0.32951.08355780.47550.7812
0.22412.08358670.47390.7853
0.16543.083511560.51050.7914
0.03444.083514450.61310.7751
0.08315.083517340.61950.7812
0.18416.083520230.66570.7812
0.08597.083523120.74880.7791

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.6.0
  • Tokenizers 0.21.1

Quellen

1 Quelle
Hugging FacePrimärVersion 4c3ec17d8d95b4597924579f9d25005743e59b2b
huggingface.co/TanAlexanderlz/RALL_RGBCROP_Aug16F-2DO2/tree/4c3ec17d8d95b4597924579f9d25005743e59b2b

Verifiziert 5. Sept.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 329 MB · SHA-256 e6f968d6eed4…9e8d · Hugging Face

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Quellenauszüge

2 Auszüge

--- 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: RALL_RGBCROP_Aug16F-2DO2 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. --> # RALL_RGBCROP_Aug16F-2DO2 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: 0.3981 - Accuracy: 0.8173 ## 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-06 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.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: 3462 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.5351 | 0.0835 | 289 | 0.6050 | 0.7444 | | 0.3295 | 1.0835 | 578 | 0.4755 | 0.7812 | | 0.2241 | 2.0835 | 867 | 0.4739 | 0.7853 | | 0.1654 | 3.0835 | 1156 | 0.5105 | 0.7914 | | 0.0344 | 4.0835 | 1445 | 0.6131 | 0.7751 | | 0.0831 | 5.0835 | 1734 | 0.6195 | 0.7812 | | 0.1841 | 6.0835 | 2023 | 0.6657 | 0.7812 | | 0.0859 | 7.0835 | 2312 | 0.7488 | 0.7791 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1

Source context: 5 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo TanAlexanderlz/RALL_RGBCROP_Aug16F-2DO2