videomae-base-short-finetuned-rwf2000
This model is a fine-tuned version of MCG-NJU/videomae-base-short on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2655
- Accuracy: 0.3714
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: 2
- eval_batch_size: 2
- 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: 3200
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3657 | 0.25 | 800 | 0.6160 | 0.7837 |
0.8426 | 1.25 | 1600 | 1.3039 | 0.665 |
0.0154 | 2.25 | 2400 | 1.3218 | 0.6937 |
0.1594 | 3.25 | 3200 | 0.9938 | 0.7575 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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