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spatial_vit_temporal_vit-finetuned-ucf101-subset
Tommidi/spatial_vit_temporal_vit-finetuned-ucf101-subset
spatial_vit_temporal_vit-finetuned-ucf101-subset is a machine learning model from Tommidi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- st_vit
- Access
- Public
- Created
- Feb 6, 2024
- Updated
- Feb 7, 2024
- SHA
- f72b6593
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. -->
spatial_vit_temporal_vit-finetuned-ucf101-subset
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3172
- Accuracy: 0.68
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: 148
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2165 | 0.26 | 38 | 2.0699 | 0.2667 |
| 1.8229 | 1.26 | 76 | 1.8160 | 0.5 |
| 1.4707 | 2.26 | 114 | 1.4157 | 0.7 |
| 1.3886 | 3.23 | 148 | 1.3520 | 0.7333 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Library
- transformers
- Type
- st_vit
- Created
- Feb 6, 2024
- Updated
- Feb 7, 2024