ViViT_quality_check-10class
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: 0.2178
- Accuracy: 1.0
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 9.3175 | 0.05 | 15 | 2.2016 | 0.2 |
| 6.5055 | 1.05 | 30 | 1.7107 | 0.4 |
| 2.1821 | 2.05 | 45 | 1.0948 | 0.8 |
| 0.4256 | 3.05 | 60 | 0.6609 | 0.9 |
| 0.0799 | 4.05 | 75 | 0.5211 | 0.9 |
| 0.0229 | 5.05 | 90 | 0.2628 | 1.0 |
| 0.0081 | 6.05 | 105 | 0.2656 | 1.0 |
| 0.0052 | 7.05 | 120 | 0.2405 | 0.9 |
| 0.0043 | 8.05 | 135 | 0.2094 | 1.0 |
| 0.0036 | 9.05 | 150 | 0.2164 | 1.0 |
| 0.003 | 10.05 | 165 | 0.2178 | 1.0 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
google/vivit-b-16x2-kinetics400