videomae-base-finetuned-lift-data-resize
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: 0.9940
- Accuracy: 0.5408
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 76
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5445 | 0.2632 | 20 | 1.6095 | 0.1123 |
| 1.2942 | 1.2632 | 40 | 1.2199 | 0.5120 |
| 1.2008 | 2.2632 | 60 | 1.1847 | 0.5267 |
| 1.0759 | 3.2105 | 76 | 1.0455 | 0.5525 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.1.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1
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Model tree for PergaZuZ/videomae-base-finetuned-lift-data-resize
Base model
MCG-NJU/videomae-base