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clip-vit-large-patch14-finetuned-fruits-360_vitlarge
AnneMarie1/clip-vit-large-patch14-finetuned-fruits-360_vitlarge
clip-vit-large-patch14-finetuned-fruits-360_vitlarge is a image classification model from AnneMarie1. 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
- vit
- Access
- Public
- Created
- Mar 29, 2023
- Updated
- Mar 29, 2023
- SHA
- 9d4ef70f
Datasets
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-fruits-360_vitlarge
This model is a fine-tuned version of openai/clip-vit-large-patch14 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0743
- Accuracy: 0.9846
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0674 | 0.98 | 48 | 0.6958 | 0.7476 |
| 0.5475 | 1.99 | 97 | 0.4484 | 0.8542 |
| 0.4065 | 2.99 | 146 | 0.2249 | 0.9274 |
| 0.2386 | 4.0 | 195 | 0.1154 | 0.9724 |
| 0.197 | 4.92 | 240 | 0.0743 | 0.9846 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Mar 29, 2023
- Updated
- Mar 29, 2023