vivit-b-16x2-kinetics400-finetuned-0505-mediapipe
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: 1.3416
- Accuracy: 0.54
Model description
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Intended uses & limitations
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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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 520
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.5013 | 0.1019 | 53 | 2.4211 | 0.1 |
2.2648 | 1.1019 | 106 | 2.2881 | 0.16 |
1.6509 | 2.1019 | 159 | 2.2324 | 0.28 |
0.6919 | 3.1019 | 212 | 1.5626 | 0.54 |
0.3172 | 4.1019 | 265 | 1.3768 | 0.56 |
0.0896 | 5.1019 | 318 | 1.3324 | 0.54 |
0.0149 | 6.1019 | 371 | 1.3616 | 0.58 |
0.0057 | 7.1019 | 424 | 1.3328 | 0.54 |
0.0029 | 8.1019 | 477 | 1.3432 | 0.58 |
0.003 | 9.0827 | 520 | 1.3416 | 0.54 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for kkumtori/vivit-b-16x2-kinetics400-finetuned-0505-mediapipe
Base model
google/vivit-b-16x2-kinetics400