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--- |
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library_name: transformers |
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base_model: openai/clip-vit-base-patch32 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: clip-ROCOv2-radiology-5ep |
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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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# clip-ROCOv2-radiology-5ep |
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This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4365 |
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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-06 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.5698 | 0.6588 | 500 | 1.4979 | |
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| 1.0335 | 1.3175 | 1000 | 1.2915 | |
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| 0.9555 | 1.9763 | 1500 | 1.1798 | |
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| 0.644 | 2.6350 | 2000 | 1.2104 | |
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| 0.3687 | 3.2938 | 2500 | 1.3033 | |
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| 0.3659 | 3.9526 | 3000 | 1.3342 | |
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| 0.2289 | 4.6113 | 3500 | 1.4365 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 4.4.1 |
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- Tokenizers 0.19.1 |
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