Model save

README.md

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+---
+library_name: transformers
+license: other
+base_model: google/medsiglip-448
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+model-index:
+- name: medsiglip-448-ft-crc100k
+  results: []
+---
+
+<!-- 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. -->
+
+# medsiglip-448-ft-crc100k
+
+This model is a fine-tuned version of [google/medsiglip-448](https://huggingface.co/google/medsiglip-448) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2713
+
+## 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 5
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3465        | 0.3556 | 50   | 1.3722          |
+| 1.3101        | 0.7111 | 100  | 1.3356          |
+| 1.3028        | 1.064  | 150  | 1.2855          |
+| 1.2389        | 1.4196 | 200  | 1.3003          |
+| 1.2522        | 1.7751 | 250  | 1.2713          |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.5.1+cu121
+- Datasets 4.0.0
+- Tokenizers 0.21.0