Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
+datasets:
+- medmnist-v2
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: pneumoniamnist-beit-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. -->
+
+# pneumoniamnist-beit-base-finetuned
+
+This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the medmnist-v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3569
+- Accuracy: 0.8569
+- Precision: 0.8111
+- Recall: 0.8649
+- F1: 0.8292
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.5947        | 0.9898 | 73   | 0.5165          | 0.7424   | 0.3712    | 0.5    | 0.4261 |
+| 0.4888        | 1.9932 | 147  | 0.3450          | 0.8569   | 0.8116    | 0.8190 | 0.8151 |
+| 0.4022        | 2.9966 | 221  | 0.4225          | 0.8340   | 0.7914    | 0.8567 | 0.8079 |
+| 0.4319        | 4.0    | 295  | 0.3600          | 0.8588   | 0.8123    | 0.8589 | 0.8292 |
+| 0.3836        | 4.9898 | 368  | 0.3665          | 0.8511   | 0.8054    | 0.8610 | 0.8233 |
+| 0.3887        | 5.9932 | 442  | 0.3667          | 0.8645   | 0.8197    | 0.8749 | 0.8383 |
+| 0.3947        | 6.9966 | 516  | 0.3951          | 0.8531   | 0.8098    | 0.8744 | 0.8283 |
+| 0.3741        | 8.0    | 590  | 0.3449          | 0.8683   | 0.8229    | 0.8678 | 0.8398 |
+| 0.3964        | 8.9898 | 663  | 0.3625          | 0.8588   | 0.8128    | 0.8638 | 0.8305 |
+| 0.3845        | 9.8983 | 730  | 0.3569          | 0.8569   | 0.8111    | 0.8649 | 0.8292 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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