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Picth Vision Checkpoint 6

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: 0.2964 Accuracy: 0.9664

TypeOtherModèle de baseMCG-NJU/videomae-base-finetuned-kineticsVersionRevision ac2e785CClasse

Source du modèle

Type
Other
Taille du fichier
329 MB
Modèle de base
MCG-NJU/videomae-base-finetuned-kinetics
Version
vRevision ac2e785
Mis à jour
15 oct. 2026
Téléchargements
5
Source
Hugging Face

Description de la source

picth_vision_checkpoint_6

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: 0.2964
  • Accuracy: 0.9664

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: 3912

Training results

Training LossEpochStepValidation LossAccuracy
0.00270.333613050.19740.9753
0.00751.333626100.13160.9798
0.02.332839120.29640.9664

Framework versions

  • Transformers 4.56.0
  • Pytorch 2.6.0+cu124
  • Datasets 4.0.0
  • Tokenizers 0.22.0

Sources

1 source
Hugging FacePrincipalVersion ac2e785531da736c323a425de866e71a5d382790
huggingface.co/miladfa7/picth_vision_checkpoint_6/tree/ac2e785531da736c323a425de866e71a5d382790

Vérifié 28 août

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 329 MB · SHA-256 d45296bdd4f5…1a6d · 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: picth_vision_checkpoint_6 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. --> # picth_vision_checkpoint_6 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: 0.2964 - Accuracy: 0.9664 ## 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: 3912 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.0027 | 0.3336 | 1305 | 0.1974 | 0.9753 | | 0.0075 | 1.3336 | 2610 | 0.1316 | 0.9798 | | 0.0 | 2.3328 | 3912 | 0.2964 | 0.9664 | ### Framework versions - Transformers 4.56.0 - Pytorch 2.6.0+cu124 - Datasets 4.0.0 - Tokenizers 0.22.0

Source context: 5 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo miladfa7/picth_vision_checkpoint_6