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README.md
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---
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library_name: transformers
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license: other
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base_model: google/medsiglip-448
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tags:
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- generated_from_trainer
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model-index:
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- name: medsiglip-448-cied-650-binary-classification
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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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# medsiglip-448-cied-650-binary-classification
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This model is a fine-tuned version of [google/medsiglip-448](https://huggingface.co/google/medsiglip-448) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.7149
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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: 0.001
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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: 8
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- total_train_batch_size: 128
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 5
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 7.3163 | 1.0 | 5 | 8.6896 |
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| 5.8702 | 2.0 | 10 | 3.7810 |
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| 4.3275 | 3.0 | 15 | 3.9249 |
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| 3.7694 | 4.0 | 20 | 3.7549 |
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| 3.7601 | 5.0 | 25 | 3.7149 |
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| 3.7215 | 6.0 | 30 | 3.7158 |
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| 3.7119 | 7.0 | 35 | 3.7149 |
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| 3.7088 | 8.0 | 40 | 3.7150 |
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| 3.7067 | 9.0 | 45 | 3.7159 |
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| 3.703 | 10.0 | 50 | 3.7149 |
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| 3.7032 | 11.0 | 55 | 3.7150 |
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| 3.7017 | 12.0 | 60 | 3.7149 |
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| 3.7019 | 13.0 | 65 | 3.7149 |
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| 3.7014 | 14.0 | 70 | 3.7149 |
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| 3.7012 | 15.0 | 75 | 3.7149 |
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### Framework versions
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- Transformers 4.57.3
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- Pytorch 2.9.0+cu126
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- Datasets 4.4.2
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- Tokenizers 0.22.1
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