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Picth Vision Checkpoint 1

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: 0.0552 Accuracy: 0.9939

TipoOtherModelo baseMCG-NJU/videomae-base-finetuned-kineticsVersãoRevision 5cb483cBnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
329 MB
Modelo base
MCG-NJU/videomae-base-finetuned-kinetics
Versão
vRevision 5cb483c
Atualizado
3 de nov. de 2026
Downloads
11
Fonte
Hugging Face

Descrição da fonte

picth_vision_checkpoint_1

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: 0.0552
  • Accuracy: 0.9939

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: 4
  • eval_batch_size: 4
  • 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: 12296

Training results

Training LossEpochStepValidation LossAccuracy
0.01980.250130750.08920.9847
0.04591.250161500.03680.9928
0.02.250192250.04710.9939
0.03.2498122960.05520.9939

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.3.1+cu121
  • Datasets 3.6.0
  • Tokenizers 0.21.1

Fontes

1 fonte
Hugging FacePrimárioVersão 5cb483cc52373a8ad8cfec49f8b5588fbf0e291f
huggingface.co/miladfa7/picth_vision_checkpoint_1/tree/5cb483cc52373a8ad8cfec49f8b5588fbf0e291f

Verificado 3 de nov.

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Repository files

File inventory only; completeness is unverified.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · FP32 (unverified) · 329 MB · SHA-256 50121f5bb5b7…cec1 · Hugging Face

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Trechos de fonte

3 trechos

--- 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_1 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_1 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: 0.0552 - Accuracy: 0.9939 ## 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: 4 - eval_batch_size: 4 - 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: 12296 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:-----:|:---------------:|:--------:| | 0.0198 | 0.2501 | 3075 | 0.0892 | 0.9847 | | 0.0459 | 1.2501 | 6150 | 0.0368 | 0.9928 | | 0.0 | 2.2501 | 9225 | 0.0471 | 0.9939 | | 0.0 | 3.2498 | 12296 | 0.0552 | 0.9939 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.3.1+cu121 - Datasets 3.6.0 - Tokenizers 0.21.1

Source context: 11 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo miladfa7/picth_vision_checkpoint_1

Source context: 6 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo miladfa7/picth_vision_checkpoint_1