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xclip-base-patch32-finetuned-SLT-subset
asmaa1/xclip-base-patch32-finetuned-SLT-subset
xclip-base-patch32-finetuned-SLT-subset is a video classification model from asmaa1. 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. --
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At a glance
- Task
- Video Classification
- Library
- transformers
- License
- mit
- Model type
- videomae
- Access
- Public
- Created
- Sep 27, 2023
- Updated
- Sep 27, 2023
- SHA
- 26bd881e
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. -->
xclip-base-patch32-finetuned-SLT-subset
This model is a fine-tuned version of microsoft/xclip-base-patch32 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2063
- Accuracy: 0.05
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: 1
- eval_batch_size: 1
- 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: 80
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 5.3738 | 0.25 | 20 | 3.2214 | 0.05 |
| 4.0026 | 1.25 | 40 | 3.1167 | 0.05 |
| 3.3822 | 2.25 | 60 | 3.0319 | 0.05 |
| 3.1538 | 3.25 | 80 | 3.0141 | 0.05 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- mit
- Created
- Sep 27, 2023
- Updated
- Sep 27, 2023