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BxSD Finetuned UCF RGBCROP 5e6 Poly

This model is a fine-tuned version of TanAlexanderlz/BxSDRGBCROPAug16F-8B16F5e6-poly on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.3295 Accuracy: 0.8056

Sourcehuggingface.co/TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly/tree/a1479caeabe1aad7d96d4c546cd238d6d1f3c3ee
TypeOtherModèle de baseTanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-polyVersionRevision a1479caBClasse

Source du modèle

Type
Other
Taille du fichier
329 MB
Modèle de base
TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly
Version
vRevision a1479ca
Mis à jour
19 sept. 2026
Téléchargements
49
Source
Hugging Face

Description de la source

BxSD-finetuned-UCF_RGBCROP_5e6-poly

This model is a fine-tuned version of TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3295
  • Accuracy: 0.8056

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: 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: polynomial
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 345

Training results

Training LossEpochStepValidation LossAccuracy
0.53860.0696240.54260.7619
0.28411.0696480.46810.8333
0.01532.0696720.35770.9048
0.00343.0696960.48620.9048
0.00144.06961200.45870.9048
0.00115.06961440.44340.9286
0.00096.06961680.46690.9286
0.00087.06961920.48410.9286
0.00078.06962160.46400.9286
0.00069.06962400.47200.9286
0.000610.06962640.47270.9286
0.000611.06962880.48040.9286
0.000512.06963120.48180.9286
0.000513.06963360.48280.9286
0.000614.02613450.48250.9286

Framework versions

  • Transformers 4.52.2
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1

Sources

1 source
Hugging FacePrincipalVersion a1479caeabe1aad7d96d4c546cd238d6d1f3c3ee
huggingface.co/TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly/tree/a1479caeabe1aad7d96d4c546cd238d6d1f3c3ee

Vérifié 5 sept.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 329 MB · SHA-256 ff7b832b875c…50e5 · Hugging Face

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Extraits de sources

2 extraits
Readme5 sept.huggingface.co/TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly

--- library_name: transformers license: cc-by-nc-4.0 base_model: TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly tags: - generated_from_trainer metrics: - accuracy model-index: - name: BxSD-finetuned-UCF_RGBCROP_5e6-poly 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. --> # BxSD-finetuned-UCF_RGBCROP_5e6-poly This model is a fine-tuned version of [TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly](https://huggingface.co/TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3295 - Accuracy: 0.8056 ## 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: 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: polynomial - lr_scheduler_warmup_ratio: 0.1 - training_steps: 345 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 0.5386 | 0.0696 | 24 | 0.5426 | 0.7619 | | 0.2841 | 1.0696 | 48 | 0.4681 | 0.8333 | | 0.0153 | 2.0696 | 72 | 0.3577 | 0.9048 | | 0.0034 | 3.0696 | 96 | 0.4862 | 0.9048 | | 0.0014 | 4.0696 | 120 | 0.4587 | 0.9048 | | 0.0011 | 5.0696 | 144 | 0.4434 | 0.9286 | | 0.0009 | 6.0696 | 168 | 0.4669 | 0.9286 | | 0.0008 | 7.0696 | 192 | 0.4841 | 0.9286 | | 0.0007 | 8.0696 | 216 | 0.4640 | 0.9286 | | 0.0006 | 9.0696 | 240 | 0.4720 | 0.9286 | | 0.0006 | 10.0696 | 264 | 0.4727 | 0.9286 | | 0.0006 | 11.0696 | 288 | 0.4804 | 0.9286 | | 0.0005 | 12.0696 | 312 | 0.4818 | 0.9286 | | 0.0005 | 13.0696 | 336 | 0.4828 | 0.9286 | | 0.0006 | 14.0261 | 345 | 0.4825 | 0.9286 | ### Framework versions - Transformers 4.52.2 - Pytorch 2.6.0+cu124 - Datasets 2.14.4 - Tokenizers 0.21.1

Note5 sept.huggingface.co/TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly

Source context: 49 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly