videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0826
- Accuracy: 0.9857
- F1: 0.9858
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: 8
- eval_batch_size: 8
- seed: 42
- 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: 148
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4261 | 0.2568 | 38 | 0.4304 | 0.8286 | 0.7838 |
| 0.1438 | 1.2568 | 76 | 0.2029 | 0.9143 | 0.9114 |
| 0.0618 | 2.2568 | 114 | 0.1453 | 0.9429 | 0.9427 |
| 0.034 | 3.2297 | 148 | 0.0826 | 0.9857 | 0.9858 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1
- Datasets 2.19.1
- Tokenizers 0.20.0
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Model tree for tenFnAN/videomae-base-finetuned-ucf101-subset
Base model
MCG-NJU/videomae-base