vivit-vivit-d2
This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0210
- Accuracy: 0.3496
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use 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: 6650
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.8445 | 0.1 | 665 | 2.2783 | 0.2615 |
| 2.1562 | 1.1 | 1330 | 2.2367 | 0.3635 |
| 2.2654 | 2.1 | 1995 | 1.9989 | 0.4808 |
| 2.0538 | 3.1 | 2660 | 2.4479 | 0.3778 |
| 1.1013 | 4.1 | 3325 | 2.5521 | 0.3876 |
| 0.8297 | 5.1 | 3990 | 2.8096 | 0.3955 |
| 0.5534 | 6.1 | 4655 | 2.7355 | 0.3491 |
| 0.3153 | 7.1 | 5320 | 3.0770 | 0.3477 |
| 0.6072 | 8.1 | 5985 | 2.8821 | 0.3477 |
| 1.3843 | 9.1 | 6650 | 3.0210 | 0.3496 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3