videomae-base-finetuned-kinetics-final-contest-baole3-0705
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3846
- Accuracy: 0.9083
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: 9e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 2057
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7136 | 0.0914 | 188 | 0.9178 | 0.7615 |
0.0707 | 1.0914 | 376 | 0.5263 | 0.8303 |
0.1033 | 2.0914 | 564 | 0.4823 | 0.8670 |
0.0055 | 3.0914 | 752 | 0.4533 | 0.8945 |
0.0295 | 4.0914 | 940 | 0.4714 | 0.8807 |
0.0011 | 5.0914 | 1128 | 0.4415 | 0.8853 |
0.0013 | 6.0914 | 1316 | 0.4121 | 0.8853 |
0.0007 | 7.0914 | 1504 | 0.4474 | 0.8945 |
0.0008 | 8.0914 | 1692 | 0.3972 | 0.9083 |
0.0006 | 9.0914 | 1880 | 0.3841 | 0.9083 |
0.0005 | 10.0860 | 2057 | 0.3846 | 0.9083 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for bluebird089/videomae-base-finetuned-kinetics-final-contest-baole3-0705
Base model
MCG-NJU/videomae-base-finetuned-kinetics