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ALL RGBCROP Aug16F 8B16F

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: 0.6543 Accuracy: 0.8503

KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 4e4ab46

Model source

Kind
Other
File size
329 MB
Base model
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 4e4ab46
Updated
Sep 26, 2026
Downloads
2
Source
Hugging Face

Source description

ALL_RGBCROP_Aug16F-8B16F

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: 0.6543
  • Accuracy: 0.8503

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 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: 2880

Training results

Training LossEpochStepValidation LossAccuracy
0.38870.12880.65690.8110
0.03451.15760.89160.8496
0.01172.18641.06670.8374
0.00013.111521.54950.7764

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1

Sources

1 source
Hugging FacePrimaryVersion 4e4ab4634ad50bebb2fea6aced15cdf47669c85a
huggingface.co/TanAlexanderlz/ALL_RGBCROP_Aug16F-8B16F/tree/4e4ab4634ad50bebb2fea6aced15cdf47669c85a

Verified Sep 12

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 acc47ae74d8e…1c74 · 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-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: ALL_RGBCROP_Aug16F-8B16F 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. --> # ALL_RGBCROP_Aug16F-8B16F 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: 0.6543 - Accuracy: 0.8503 ## 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 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: 2880 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3887 | 0.1 | 288 | 0.6569 | 0.8110 | | 0.0345 | 1.1 | 576 | 0.8916 | 0.8496 | | 0.0117 | 2.1 | 864 | 1.0667 | 0.8374 | | 0.0001 | 3.1 | 1152 | 1.5495 | 0.7764 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 2.14.4 - Tokenizers 0.21.1

Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo TanAlexanderlz/ALL_RGBCROP_Aug16F-8B16F