videomae-base-finetuned-movienet

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: 1.2558
  • eval_accuracy: 0.6823
  • eval_runtime: 120.548
  • eval_samples_per_second: 1.593
  • eval_steps_per_second: 0.199
  • epoch: 6.1
  • step: 1266

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: 0.1
  • training_steps: 1480

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.1
  • Tokenizers 0.13.3
Downloads last month
21
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for dvs/videomae-base-finetuned-movienet

Finetuned
(421)
this model
Finetunes
1 model