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meat_calssify_fresh_V_0_5_test
talli96123/meat_calssify_fresh_V_0_5_test
meat_calssify_fresh_V_0_5_test is a image classification model from talli96123. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Jun 5, 2024
- Updated
- Jun 5, 2024
- SHA
- c581b7f6
Base models
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. -->
meat_calssify_fresh_V_0_5_test
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 2.7620
- 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: 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
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1661 | 1.0 | 44 | 1.1896 | 0.1667 |
| 1.032 | 2.0 | 88 | 1.2389 | 0.25 |
| 1.0784 | 3.0 | 132 | 1.0699 | 0.25 |
| 1.0819 | 4.0 | 176 | 1.2184 | 0.0833 |
| 1.0274 | 5.0 | 220 | 1.4634 | 0.0833 |
| 1.106 | 6.0 | 264 | 1.0843 | 0.4167 |
| 1.1051 | 7.0 | 308 | 1.1752 | 0.25 |
| 1.0964 | 8.0 | 352 | 1.3698 | 0.1667 |
| 1.1467 | 9.0 | 396 | 1.3023 | 0.1667 |
| 0.7936 | 10.0 | 440 | 1.4005 | 0.25 |
| 0.8262 | 11.0 | 484 | 1.2786 | 0.25 |
| 1.1219 | 12.0 | 528 | 1.4314 | 0.25 |
| 0.9306 | 13.0 | 572 | 1.9908 | 0.1667 |
| 1.2061 | 14.0 | 616 | 1.4193 | 0.25 |
| 0.7925 | 15.0 | 660 | 2.1698 | 0.25 |
| 0.104 | 16.0 | 704 | 2.2744 | 0.25 |
| 0.2619 | 17.0 | 748 | 1.7998 | 0.3333 |
| 0.3196 | 18.0 | 792 | 2.0410 | 0.3333 |
| 1.2972 | 19.0 | 836 | 1.4657 | 0.5 |
| 0.7459 | 20.0 | 880 | 2.4774 | 0.3333 |
| 0.4766 | 21.0 | 924 | 2.0181 | 0.3333 |
| 0.1264 | 22.0 | 968 | 2.6095 | 0.25 |
| 0.2541 | 23.0 | 1012 | 2.6884 | 0.1667 |
| 0.179 | 24.0 | 1056 | 2.6612 | 0.25 |
| 0.308 | 25.0 | 1100 | 1.5827 | 0.5 |
| 0.0291 | 26.0 | 1144 | 2.4500 | 0.3333 |
| 0.0773 | 27.0 | 1188 | 2.4238 | 0.4167 |
| 0.0235 | 28.0 | 1232 | 1.8948 | 0.5 |
| 0.1782 | 29.0 | 1276 | 1.7855 | 0.5 |
| 0.0597 | 30.0 | 1320 | 2.7620 | 0.3333 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jun 5, 2024
- Updated
- Jun 5, 2024