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clip-vit-large-patch14-finetuned-clip-vit-large-patch14-mnist
tangg555/clip-vit-large-patch14-finetuned-clip-vit-large-patch14-mnist
clip-vit-large-patch14-finetuned-clip-vit-large-patch14-mnist is a image classification model from tangg555. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- clip
- Access
- Public
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024
- SHA
- c010c4ed
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. -->
clip-vit-large-patch14-finetuned-clip-vit-large-patch14-mnist
This model is a fine-tuned version of openai/clip-vit-large-patch14 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0268
- Accuracy: 0.9917
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: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4312 | 0.9953 | 105 | 0.0539 | 0.9862 |
| 0.3224 | 2.0 | 211 | 0.0410 | 0.987 |
| 0.2945 | 2.9858 | 315 | 0.0268 | 0.9917 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- clip
- Created
- Sep 3, 2024
- Updated
- Sep 3, 2024