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videomae-base-finetuned-numbers-augmented2
latif98/videomae-base-finetuned-numbers-augmented2
videomae-base-finetuned-numbers-augmented2 is a video classification model from latif98. 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
- May 3, 2024
- Updated
- May 4, 2024
- SHA
- c94a1a4f
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. -->
videomae-base-finetuned-numbers-augmented2
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: 0.1392
- Accuracy: 0.9681
- F1: 0.9680
- Precision: 0.9692
- Recall: 0.9678
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: 6756
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.3906 | 0.0833 | 563 | 1.2362 | 0.5628 | 0.5561 | 0.6171 | 0.5623 |
| 0.7242 | 1.0833 | 1126 | 0.8677 | 0.6867 | 0.6787 | 0.7247 | 0.6847 |
| 0.5625 | 2.0833 | 1689 | 0.6211 | 0.7883 | 0.7865 | 0.8163 | 0.7871 |
| 0.5111 | 3.0833 | 2252 | 0.4169 | 0.8623 | 0.8621 | 0.8814 | 0.8631 |
| 0.1224 | 4.0833 | 2815 | 0.2908 | 0.9036 | 0.9030 | 0.9077 | 0.9038 |
| 0.0561 | 5.0833 | 3378 | 0.2836 | 0.9208 | 0.9207 | 0.9252 | 0.9210 |
| 0.0028 | 6.0833 | 3941 | 0.2256 | 0.9466 | 0.9470 | 0.9488 | 0.9471 |
| 0.0009 | 7.0833 | 4504 | 0.1670 | 0.9673 | 0.9676 | 0.9702 | 0.9665 |
| 0.0336 | 8.0833 | 5067 | 0.1362 | 0.9656 | 0.9656 | 0.9674 | 0.9650 |
| 0.0004 | 9.0833 | 5630 | 0.1192 | 0.9776 | 0.9778 | 0.9793 | 0.9771 |
| 0.0004 | 10.0833 | 6193 | 0.1204 | 0.9725 | 0.9725 | 0.9745 | 0.9719 |
| 0.0003 | 11.0833 | 6756 | 0.1268 | 0.9725 | 0.9723 | 0.9738 | 0.9719 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- May 3, 2024
- Updated
- May 4, 2024