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Videomae Base Finetuned Movienet Take2 Finetuned Movienet Take3

This model is a fine-tuned version of dvs/videomae-base-finetuned-movienet-take2 on an unknown dataset. It achieves the following results on the evaluation set: evalloss: 1.4087 evalaccuracy: 0.7396 evalruntime:...

KindOtherBase modeldvs/videomae-base-finetuned-movienet-take2VersionRevision 98b912b

Model source

Kind
Other
File size
329 MB
Base model
dvs/videomae-base-finetuned-movienet-take2
Version
vRevision 98b912b
Updated
Sep 18, 2026
Downloads
11
Source
Hugging Face

Source description

videomae-base-finetuned-movienet-take2-finetuned-movienet-take3

This model is a fine-tuned version of dvs/videomae-base-finetuned-movienet-take2 on an unknown dataset. It achieves the following results on the evaluation set:

  • eval_loss: 1.4087
  • eval_accuracy: 0.7396
  • eval_runtime: 167.2166
  • eval_samples_per_second: 1.148
  • eval_steps_per_second: 0.144
  • epoch: 3.02
  • step: 631

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.3
  • training_steps: 2960

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3

Sources

1 source

Model artifacts

2 artifacts

model.safetensors

safetensors · 329 MB · SHA-256 044d8c9e828f…b48b · Hugging Face

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pytorch_model.bin

bin · 329 MB · SHA-256 5ff6409d9539…69ae · Hugging Face

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Source excerpts

2 excerpts

--- license: cc-by-nc-4.0 base_model: dvs/videomae-base-finetuned-movienet-take2 tags: - generated_from_trainer model-index: - name: videomae-base-finetuned-movienet-take2-finetuned-movienet-take3 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. --> # videomae-base-finetuned-movienet-take2-finetuned-movienet-take3 This model is a fine-tuned version of [dvs/videomae-base-finetuned-movienet-take2](https://huggingface.co/dvs/videomae-base-finetuned-movienet-take2) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 1.4087 - eval_accuracy: 0.7396 - eval_runtime: 167.2166 - eval_samples_per_second: 1.148 - eval_steps_per_second: 0.144 - epoch: 3.02 - step: 631 ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.3 - training_steps: 2960 ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.1 - Tokenizers 0.13.3

Source context: 11 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo dvs/videomae-base-finetuned-movienet-take2-finetuned-movienet-take3