Downloads · 30 days
69
2% of all-time downloads
vivit-b-16x2-kinetics400-UCF-Crime
prathameshdalal/vivit-b-16x2-kinetics400-UCF-Crime
vivit-b-16x2-kinetics400-UCF-Crime is a video classification model from prathameshdalal. 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 mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
4.3K
Public
Parameters
88.7M
3.2 GB on disk
Likes
1
Public
Repo makeup
Click a slice to open those files.
.bin355 MB · 50%
At a glance
- Task
- Video Classification
- Library
- transformers
- License
- mit
- Model type
- vivit
- Access
- Public
- Created
- Sep 22, 2023
- Updated
- Nov 5, 2024
- SHA
- 486229be
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. -->
vivit-b-16x2-kinetics400-UCF-Crime
This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on UCF-Crime dataset. It achieves the following results on the evaluation set:
- Loss: 1.9757
- Accuracy: 0.6149
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: 3132
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2072 | 0.06 | 196 | 1.6400 | 0.5518 |
| 1.5513 | 1.06 | 392 | 1.4988 | 0.5634 |
| 1.1038 | 2.06 | 588 | 1.5328 | 0.5861 |
| 0.9462 | 3.06 | 784 | 1.3932 | 0.6178 |
| 0.7387 | 4.06 | 980 | 1.5449 | 0.6060 |
| 0.5085 | 5.06 | 1176 | 1.3075 | 0.6287 |
| 0.4443 | 6.06 | 1372 | 1.6743 | 0.6001 |
| 0.4695 | 7.06 | 1568 | 1.5287 | 0.6172 |
| 0.4409 | 8.06 | 1764 | 1.7749 | 0.6089 |
| 0.1158 | 9.06 | 1960 | 1.9027 | 0.6076 |
| 0.1183 | 10.06 | 2156 | 1.9622 | 0.6085 |
| 0.1322 | 11.06 | 2352 | 2.0872 | 0.6152 |
| 0.1881 | 12.06 | 2548 | 2.0095 | 0.6094 |
| 0.0932 | 13.06 | 2744 | 1.9398 | 0.6232 |
| 0.0303 | 14.06 | 2940 | 1.9994 | 0.6134 |
| 0.0513 | 15.06 | 3132 | 1.9757 | 0.6149 |
Framework versions
- Transformers 4.33.2
- Pytorch 1.10.0+cu113
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Video Classification
- Library
- transformers
- Type
- vivit
- License
- mit
- Created
- Sep 22, 2023
- Updated
- Nov 5, 2024