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RALL RGBCROP Aug16F 1DO1

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: 0.6522 Accuracy: 0.8173

Sourcehuggingface.co/TanAlexanderlz/RALL_RGBCROP_Aug16F-1DO1/tree/4fad9e743cf54841fe39c316e6d5ff04304d4bd8
KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 4fad9e7Cgrade

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 4fad9e7
Updated
Sep 21, 2026
Downloads
2
Source
Hugging Face

Source description

RALL_RGBCROP_Aug16F-1DO1

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: 0.6522
  • 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
0.52630.08352890.63510.6135
0.25451.08355780.49650.7812
0.12612.08358670.52610.8098
0.07533.083511560.62600.8160
0.02464.083514450.75910.8160
0.05875.083517340.84680.8221
0.03516.083520230.89520.8180
0.0017.083523121.00940.8098
0.00388.083526011.05830.8200
0.00119.083528901.06320.8119

Framework versions

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

Sources

1 source
Hugging FacePrimaryVersion 4fad9e743cf54841fe39c316e6d5ff04304d4bd8
huggingface.co/TanAlexanderlz/RALL_RGBCROP_Aug16F-1DO1/tree/4fad9e743cf54841fe39c316e6d5ff04304d4bd8

Verified Sep 5

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 0ff67480bb1a…ca7a · Hugging Face

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Source excerpts

2 excerpts
ReadmeSep 5huggingface.co/TanAlexanderlz/RALL_RGBCROP_Aug16F-1DO1

--- 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-1DO1 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-1DO1 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: 0.6522 - 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 | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.5263 | 0.0835 | 289 | 0.6351 | 0.6135 | | 0.2545 | 1.0835 | 578 | 0.4965 | 0.7812 | | 0.1261 | 2.0835 | 867 | 0.5261 | 0.8098 | | 0.0753 | 3.0835 | 1156 | 0.6260 | 0.8160 | | 0.0246 | 4.0835 | 1445 | 0.7591 | 0.8160 | | 0.0587 | 5.0835 | 1734 | 0.8468 | 0.8221 | | 0.0351 | 6.0835 | 2023 | 0.8952 | 0.8180 | | 0.001 | 7.0835 | 2312 | 1.0094 | 0.8098 | | 0.0038 | 8.0835 | 2601 | 1.0583 | 0.8200 | | 0.0011 | 9.0835 | 2890 | 1.0632 | 0.8119 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1

NoteSep 5huggingface.co/TanAlexanderlz/RALL_RGBCROP_Aug16F-1DO1

Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo TanAlexanderlz/RALL_RGBCROP_Aug16F-1DO1