Model save

README.md

@@ -0,0 +1,82 @@
+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: microsoft/swin-large-patch4-window7-224-in22k
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: organamnist-swin-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-swin-base-finetuned
+
+This model is a fine-tuned version of [microsoft/swin-large-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-large-patch4-window7-224-in22k) on the medmnist-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0433
+- Accuracy: 0.9846
+- Precision: 0.9888
+- Recall: 0.9864
+- F1: 0.9874
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.6172        | 1.0   | 540  | 0.1913          | 0.9373   | 0.9481    | 0.9427 | 0.9422 |
+| 0.6346        | 2.0   | 1081 | 0.0756          | 0.9760   | 0.9799    | 0.9752 | 0.9770 |
+| 0.6405        | 3.0   | 1621 | 0.1310          | 0.9553   | 0.9600    | 0.9515 | 0.9537 |
+| 0.5005        | 4.0   | 2162 | 0.1138          | 0.9663   | 0.9757    | 0.9718 | 0.9729 |
+| 0.5669        | 5.0   | 2702 | 0.1142          | 0.9603   | 0.9704    | 0.9647 | 0.9665 |
+| 0.5548        | 6.0   | 3243 | 0.0569          | 0.9772   | 0.9812    | 0.9785 | 0.9795 |
+| 0.4298        | 7.0   | 3783 | 0.0989          | 0.9663   | 0.9770    | 0.9723 | 0.9736 |
+| 0.3932        | 8.0   | 4324 | 0.0335          | 0.9884   | 0.9903    | 0.9887 | 0.9894 |
+| 0.3409        | 9.0   | 4864 | 0.0371          | 0.9878   | 0.9900    | 0.9877 | 0.9887 |
+| 0.3111        | 9.99  | 5400 | 0.0433          | 0.9846   | 0.9888    | 0.9864 | 0.9874 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ab78d3291c01e4242fb73d1296e185579de938ec3b3559da6ad9b660e34f5da4
+oid sha256:2bc2969fba89d0542e2a6403af01337eaff443596362b0230478f46e6bcb4181
 size 4702620