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videomae-base-finetuned
xixi1031/videomae-base-finetuned
videomae-base-finetuned is a machine learning model from xixi1031. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- videomae
- Access
- Public
- Created
- Aug 7, 2024
- Updated
- Aug 13, 2024
- SHA
- 5612ae88
Model card
From the Hugging Face model README
<!-- 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
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6501
- Accuracy: 0.7114
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: 865
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2839 | 0.2012 | 174 | 1.3653 | 0.5232 |
| 0.2579 | 1.2012 | 348 | 0.6861 | 0.7335 |
| 0.2075 | 2.2012 | 522 | 0.9429 | 0.6264 |
| 0.1305 | 3.2012 | 696 | 1.4886 | 0.5421 |
| 0.1022 | 4.1954 | 865 | 2.0678 | 0.4938 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- videomae
- Created
- Aug 7, 2024
- Updated
- Aug 13, 2024