Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: facebook/deit-base-patch16-224
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: organamnist-deit-base-finetuned
+  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. -->
+
+# organamnist-deit-base-finetuned
+
+This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the medmnist-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0720
+- Accuracy: 0.9835
+- Precision: 0.9888
+- Recall: 0.9882
+- F1: 0.9882
+
+## 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: 0.005
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5849        | 1.0   | 540  | 0.1842          | 0.9442   | 0.9449    | 0.9268 | 0.9285 |
+| 0.6494        | 2.0   | 1081 | 0.1433          | 0.9499   | 0.9539    | 0.9510 | 0.9509 |
+| 0.6059        | 3.0   | 1621 | 0.1171          | 0.9562   | 0.9659    | 0.9569 | 0.9593 |
+| 0.3547        | 4.0   | 2162 | 0.0981          | 0.9666   | 0.9709    | 0.9712 | 0.9702 |
+| 0.4852        | 5.0   | 2702 | 0.0539          | 0.9817   | 0.9848    | 0.9842 | 0.9842 |
+| 0.406         | 6.0   | 3243 | 0.0818          | 0.9749   | 0.9793    | 0.9752 | 0.9768 |
+| 0.3074        | 7.0   | 3783 | 0.1289          | 0.9666   | 0.9815    | 0.9778 | 0.9783 |
+| 0.2679        | 8.0   | 4324 | 0.0311          | 0.9900   | 0.9916    | 0.9909 | 0.9912 |
+| 0.2439        | 9.0   | 4864 | 0.0577          | 0.9851   | 0.9886    | 0.9880 | 0.9881 |
+| 0.2169        | 9.99  | 5400 | 0.0720          | 0.9835   | 0.9888    | 0.9882 | 0.9882 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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