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: 0.5126
- Accuracy: 0.7586
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: 16
- eval_batch_size: 16
- 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: 150
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9276 | 0.0933 | 14 | 0.8787 | 0.6207 |
| 0.8845 | 1.0933 | 28 | 0.7380 | 0.7069 |
| 0.685 | 2.0933 | 42 | 0.7084 | 0.7069 |
| 0.7556 | 3.0933 | 56 | 0.6161 | 0.8103 |
| 0.5482 | 4.0933 | 70 | 0.6827 | 0.7414 |
| 0.6461 | 5.0933 | 84 | 0.6916 | 0.7069 |
| 0.701 | 6.0933 | 98 | 0.5490 | 0.8103 |
| 0.5242 | 7.0933 | 112 | 0.5372 | 0.7931 |
| 0.4482 | 8.0933 | 126 | 0.5276 | 0.8103 |
| 0.3898 | 9.0933 | 140 | 0.5047 | 0.7931 |
| 0.3664 | 10.0667 | 150 | 0.5126 | 0.7586 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
MCG-NJU/videomae-base