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ft-videomae-ucf101
aisuko/ft-videomae-ucf101
ft-videomae-ucf101 is a video classification model from aisuko. Use it for the video classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Video Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- videomae
- Access
- Public
- Created
- Dec 15, 2023
- Updated
- Feb 29, 2024
- SHA
- 7a1023b9
Base models
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. -->
ft-videomae-ucf101
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on the aisuko/funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1498
- Accuracy: 1.0
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 150
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2519 | 0.5 | 75 | 0.1498 | 1.0 |
| 0.0746 | 1.5 | 150 | 0.0278 | 1.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Dec 15, 2023
- Updated
- Feb 29, 2024