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--- |
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base_model: openai/clip-vit-large-patch14 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Psoriasis-Project-M-clip-vit-large-patch14 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Psoriasis-Project-M-clip-vit-large-patch14 |
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This model is a fine-tuned version of [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4710 |
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- Accuracy: 0.8958 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 0.92 | 6 | 1.8042 | 0.7917 | |
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| 0.1258 | 2.0 | 13 | 1.4387 | 0.8333 | |
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| 0.1258 | 2.92 | 19 | 2.5280 | 0.7292 | |
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| 0.0815 | 4.0 | 26 | 0.9424 | 0.8542 | |
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| 0.0493 | 4.62 | 30 | 0.8434 | 0.8542 | |
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| No log | 0.92 | 6 | 8.7831 | 0.2917 | |
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| 6.4844 | 2.0 | 13 | 3.2443 | 0.5417 | |
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| 6.4844 | 2.92 | 19 | 1.4924 | 0.7708 | |
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| 1.5554 | 4.0 | 26 | 0.6663 | 0.875 | |
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| 0.2061 | 4.62 | 30 | 0.7655 | 0.8125 | |
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| No log | 0.92 | 6 | 1.1418 | 0.8333 | |
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| 0.0506 | 2.0 | 13 | 2.5893 | 0.7292 | |
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| 0.0506 | 2.92 | 19 | 1.5925 | 0.7917 | |
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| 0.1137 | 4.0 | 26 | 1.3275 | 0.8958 | |
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| 0.0132 | 4.62 | 30 | 1.4710 | 0.8958 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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