ViViT_default_fold__4__10_epoch_Aug_batch_2_4_BdSLW60
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: 1.7884
- Accuracy: 0.6889
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: 9030
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.6984 | 0.1 | 903 | 0.4381 | 0.9141 |
0.1951 | 1.1001 | 1807 | 0.0468 | 0.9826 |
0.1833 | 2.1 | 2710 | 0.0987 | 0.9751 |
0.0932 | 3.1001 | 3614 | 0.0408 | 0.9888 |
0.0198 | 4.1 | 4517 | 0.0676 | 0.9851 |
0.024 | 5.1001 | 5421 | 0.0530 | 0.9888 |
0.0038 | 6.1 | 6324 | 0.0729 | 0.9875 |
0.0026 | 7.1001 | 7228 | 0.0417 | 0.9913 |
0.004 | 8.1 | 8131 | 0.0587 | 0.9913 |
0.0045 | 9.0995 | 9030 | 0.0383 | 0.9900 |
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