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