ALL_RGBCROP_ori16F-8B16F-GACWD5lrDO
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: 0.4092
- Accuracy: 0.8144
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 1920
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.694 | 0.025 | 48 | 0.7127 | 0.4939 |
0.6395 | 1.025 | 96 | 0.6772 | 0.5976 |
0.4871 | 2.025 | 144 | 0.6142 | 0.6707 |
0.4162 | 3.025 | 192 | 0.5418 | 0.7256 |
0.2336 | 4.025 | 240 | 0.5030 | 0.7622 |
0.159 | 5.025 | 288 | 0.5045 | 0.7927 |
0.1486 | 6.025 | 336 | 0.5186 | 0.7805 |
0.0997 | 7.025 | 384 | 0.5649 | 0.7866 |
0.07 | 8.025 | 432 | 0.6180 | 0.7805 |
0.0377 | 9.025 | 480 | 0.6364 | 0.7927 |
0.0103 | 10.025 | 528 | 0.7102 | 0.7866 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for TanAlexanderlz/ALL_RGBCROP_ori16F-8B16F-GACWD5lrDO
Base model
MCG-NJU/videomae-base-finetuned-kinetics