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RALL RGBCROP Ori16F 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: 0.7010 Accuracy: 0.8193

TypeOtherModèle de baseMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 130625dCClasse

Source du modèle

Type
Other
Taille du fichier
329 MB
Modèle de base
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision 130625d
Mis à jour
19 sept. 2026
Téléchargements
2
Source
Hugging Face

Description de la source

RALL_RGBCROP_ori16F-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: 0.7010
  • Accuracy: 0.8193

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: 1920

Training results

Training LossEpochStepValidation LossAccuracy
0.32290.0505970.49990.7669
0.3051.05051940.48980.8098
0.14012.05052910.94210.8221
0.00043.05053881.05500.8160
0.00314.05054851.21710.8160
0.02115.05055821.25560.8221
0.10026.05056791.14370.8160
0.00017.05057761.20520.7975

Framework versions

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

Sources

1 source
Hugging FacePrincipalVersion 130625d2c925d5ac427279192804953a66aaef5c
huggingface.co/TanAlexanderlz/RALL_RGBCROP_ori16F-8B16F/tree/130625d2c925d5ac427279192804953a66aaef5c

Vérifié 5 sept.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 329 MB · SHA-256 218a03dcfadc…27c3 · Hugging Face

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Extraits de sources

2 extraits

--- 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_ori16F-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. --> # RALL_RGBCROP_ori16F-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: 0.7010 - Accuracy: 0.8193 ## 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: 1920 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.3229 | 0.0505 | 97 | 0.4999 | 0.7669 | | 0.305 | 1.0505 | 194 | 0.4898 | 0.8098 | | 0.1401 | 2.0505 | 291 | 0.9421 | 0.8221 | | 0.0004 | 3.0505 | 388 | 1.0550 | 0.8160 | | 0.0031 | 4.0505 | 485 | 1.2171 | 0.8160 | | 0.0211 | 5.0505 | 582 | 1.2556 | 0.8221 | | 0.1002 | 6.0505 | 679 | 1.1437 | 0.8160 | | 0.0001 | 7.0505 | 776 | 1.2052 | 0.7975 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1

Source context: 2 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo TanAlexanderlz/RALL_RGBCROP_ori16F-8B16F