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metadata
tags:
  - generated_from_trainer
metrics:
  - rouge
  - bleu
model-index:
  - name: timesformer-bert-video-captioning
    results: []

timesformer-bert-video-captioning

This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2821
  • Rouge1: 30.0468
  • Rouge2: 8.4998
  • Rougel: 29.0632
  • Rougelsum: 29.0231
  • Bleu: 4.8298
  • Gen Len: 9.5332

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
  • num_epochs: 2

Training results

Training Loss Epoch Step Bleu Gen Len Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.4961 0.12 200 1.5879 9.5332 1.6548 25.4717 5.11 24.6679 24.6696
1.6561 0.25 400 2.3515 9.5332 1.5339 26.1748 5.9106 25.413 25.3958
1.5772 0.37 600 2.266 9.5332 1.4510 28.6891 6.0431 27.7387 27.8043
1.492 0.49 800 3.6517 9.5332 1.3760 29.0257 7.8515 28.3142 28.3036
1.4736 0.61 1000 3.4866 9.5332 1.3425 27.9774 6.2175 26.7783 26.7207
1.3856 0.74 1200 3.1649 9.5332 1.3118 27.3532 6.5569 26.4964 26.5087
1.3972 0.86 1400 3.5337 9.5332 1.2868 28.233 7.6471 27.3651 27.3354
1.374 0.98 1600 3.5737 9.5332 1.2571 28.8216 7.542 27.9166 27.9353
1.2207 1.1 1800 3.7983 9.5332 1.3362 29.9574 8.1088 28.8866 28.855
1.1861 1.23 2000 3.6521 9.5332 1.3295 30.072 7.7799 28.8417 28.864
1.1173 1.35 2200 3.9784 9.5332 1.3335 29.736 7.9661 28.6877 28.6974
1.1255 1.47 2400 4.3021 9.5332 1.3097 29.8176 8.4656 28.958 28.9571
1.0909 1.6 2600 1.3095 30.0233 8.4896 29.2562 29.2375 4.4782 9.5332
1.1205 1.72 2800 1.2992 29.7164 8.007 28.5027 28.5018 4.44 9.5332
1.1069 1.84 3000 1.2830 29.851 8.4312 28.8139 28.8205 4.6065 9.5332
1.076 1.96 3200 1.2821 30.0468 8.4998 29.0632 29.0231 4.8298 9.5332

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3