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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: 0.7329 Accuracy: 0.5333
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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:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7768 | 0.2667 | 16 | 0.7145 | 0.25 |
| 0.7144 | 1.2667 | 32 | 0.7077 | 0.5333 |
| 0.7573 | 2.2667 | 48 | 0.7484 | 0.5333 |
| 0.6849 | 3.2 | 60 | 0.7329 | 0.5333 |
--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-typing-detection results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # videomae-base-finetuned-typing-detection This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.7329 - Accuracy: 0.5333 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Use 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: 60 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.7768 | 0.2667 | 16 | 0.7145 | 0.25 | | 0.7144 | 1.2667 | 32 | 0.7077 | 0.5333 | | 0.7573 | 2.2667 | 48 | 0.7484 | 0.5333 | | 0.6849 | 3.2 | 60 | 0.7329 | 0.5333 | ### Framework versions - Transformers 4.48.3 - Pytorch 2.4.0+cu121 - Datasets 2.19.2 - Tokenizers 0.21.0
Source context: 7 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo jpablo0705/videomae-base-finetuned-typing-detection
