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finetuned-Accident-MultipleLabels-Video-subset-v2-new3
pavitemple/finetuned-Accident-MultipleLabels-Video-subset-v2-new3
finetuned-Accident-MultipleLabels-Video-subset-v2-new3 is a video classification model from pavitemple. 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 5, 2023
- Updated
- Dec 5, 2023
- SHA
- dc5c09c3
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. -->
finetuned-Accident-MultipleLabels-Video-subset-v2-new3
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: 1.7434
- Accuracy: 0.3333
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 35
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.06 | 2 | 1.9011 | 0.1719 |
| No log | 1.06 | 4 | 1.8469 | 0.3281 |
| No log | 2.06 | 6 | 1.8533 | 0.3281 |
| No log | 3.06 | 8 | 1.9122 | 0.3281 |
| 1.6429 | 4.06 | 10 | 1.9870 | 0.3125 |
| 1.6429 | 5.06 | 12 | 1.9921 | 0.2969 |
| 1.6429 | 6.06 | 14 | 1.9683 | 0.3125 |
| 1.6429 | 7.06 | 16 | 1.9313 | 0.3125 |
| 1.6429 | 8.06 | 18 | 1.9203 | 0.3125 |
| 1.4144 | 9.06 | 20 | 1.9251 | 0.3125 |
| 1.4144 | 10.06 | 22 | 1.9316 | 0.2969 |
| 1.4144 | 11.06 | 24 | 1.9455 | 0.2969 |
| 1.4144 | 12.06 | 26 | 1.9723 | 0.2969 |
| 1.4144 | 13.06 | 28 | 1.9897 | 0.2969 |
| 1.3307 | 14.06 | 30 | 2.0000 | 0.2969 |
| 1.3307 | 15.06 | 32 | 2.0063 | 0.2969 |
| 1.3307 | 16.06 | 34 | 2.0072 | 0.2969 |
| 1.3307 | 17.03 | 35 | 2.0082 | 0.2969 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.2.0.dev20231202+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Dec 5, 2023
- Updated
- Dec 5, 2023