metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ALL_RGBCROP_ori16F-8B16F-GWlr-cosine
results: []
ALL_RGBCROP_ori16F-8B16F-GWlr-cosine
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: 0.3658
- Accuracy: 0.8623
Best Checkpoint : 240
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: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1152
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6775 | 0.0417 | 48 | 0.7147 | 0.4695 |
| 0.5877 | 1.0417 | 96 | 0.6383 | 0.6220 |
| 0.3375 | 2.0417 | 144 | 0.5176 | 0.7317 |
| 0.219 | 3.0417 | 192 | 0.4915 | 0.7805 |
| 0.0698 | 4.0417 | 240 | 0.5611 | 0.8110 |
| 0.0587 | 5.0417 | 288 | 0.6506 | 0.7927 |
| 0.0194 | 6.0417 | 336 | 0.7638 | 0.7988 |
| 0.0029 | 7.0417 | 384 | 0.9139 | 0.7805 |
| 0.0023 | 8.0417 | 432 | 0.9306 | 0.7988 |
| 0.0033 | 9.0417 | 480 | 0.9203 | 0.7988 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1