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MCG NJU Finetuned

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set: evalloss: 0.6903 evalmodelpreparationtime: 0.023 evalaccuracy: 0.7143...

ArtOtherBasismodellMCG-NJU/videomae-baseVersionRevision 67846efCBewertung

Modellquelle

Art
Other
Dateigröße
329 MB
Basismodell
MCG-NJU/videomae-base
Version
vRevision 67846ef
Aktualisiert
21. Sept. 2026
Downloads
3
Quelle
Hugging Face

Quellenbeschreibung

MCG-NJU-finetuned

This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.6903
  • eval_model_preparation_time: 0.023
  • eval_accuracy: 0.7143
  • eval_runtime: 90.6818
  • eval_samples_per_second: 0.077
  • eval_steps_per_second: 0.044
  • step: 0

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: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Use 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
  • num_epochs: 3.0

Framework versions

  • Transformers 4.53.0
  • Pytorch 2.5.1+cpu
  • Datasets 3.6.0
  • Tokenizers 0.21.2

Quellen

1 Quelle
Hugging FacePrimärVersion 67846ef3c2a82c5e9be6872bbfab0a83f7d8b106
huggingface.co/ja-aj/MCG-NJU-finetuned/tree/67846ef3c2a82c5e9be6872bbfab0a83f7d8b106

Verifiziert 5. Sept.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 329 MB · SHA-256 0cf27c112235…45c3 · Hugging Face

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Quellenauszüge

2 Auszüge

--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer model-index: - name: MCG-NJU-finetuned 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. --> # MCG-NJU-finetuned This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 0.6903 - eval_model_preparation_time: 0.023 - eval_accuracy: 0.7143 - eval_runtime: 90.6818 - eval_samples_per_second: 0.077 - eval_steps_per_second: 0.044 - step: 0 ## 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: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use 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 - num_epochs: 3.0 ### Framework versions - Transformers 4.53.0 - Pytorch 2.5.1+cpu - Datasets 3.6.0 - Tokenizers 0.21.2

Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo ja-aj/MCG-NJU-finetuned