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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-ft-crc100k
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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-ft-crc100k
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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: 1.0969
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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: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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- optimizer: Use 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: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 2.0154 | 0.1696 | 50 | 1.3132 |
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| 1.2953 | 0.3393 | 100 | 1.2689 |
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| 1.2244 | 0.5089 | 150 | 1.2471 |
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| 1.2402 | 0.6785 | 200 | 1.2766 |
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| 1.2249 | 0.8482 | 250 | 1.1939 |
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| 1.2154 | 1.0170 | 300 | 1.1667 |
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| 1.1081 | 1.1866 | 350 | 1.1432 |
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| 1.1174 | 1.3562 | 400 | 1.1457 |
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| 1.1113 | 1.5259 | 450 | 1.1234 |
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| 1.1003 | 1.6955 | 500 | 1.1071 |
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| 1.0693 | 1.8651 | 550 | 1.0969 |
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### Framework versions
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- Transformers 4.56.1
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- Pytorch 2.8.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.0
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