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: breastmnist-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. -->
+
+# breastmnist-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: 0.3454
+- Accuracy: 0.8718
+- Precision: 0.8698
+- Recall: 0.7920
+- F1: 0.8194
+
+## 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     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.9143 | 8    | 0.5026          | 0.7436   | 0.8701    | 0.5238 | 0.4708 |
+| 0.6168        | 1.9429 | 17   | 0.4762          | 0.8462   | 0.8286    | 0.7594 | 0.7833 |
+| 0.5954        | 2.9714 | 26   | 0.5305          | 0.7308   | 0.3654    | 0.5    | 0.4222 |
+| 0.5934        | 4.0    | 35   | 0.4790          | 0.7692   | 0.7836    | 0.5865 | 0.5846 |
+| 0.526         | 4.9143 | 43   | 0.3693          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |
+| 0.4651        | 5.9429 | 52   | 0.4789          | 0.7949   | 0.7434    | 0.7694 | 0.7534 |
+| 0.493         | 6.9714 | 61   | 0.4187          | 0.8205   | 0.7792    | 0.7419 | 0.7565 |
+| 0.4337        | 8.0    | 70   | 0.3600          | 0.8590   | 0.8417    | 0.7832 | 0.8051 |
+| 0.4337        | 8.9143 | 78   | 0.3468          | 0.8718   | 0.8544    | 0.8070 | 0.8260 |
+| 0.418         | 9.1429 | 80   | 0.3454          | 0.8718   | 0.8698    | 0.7920 | 0.8194 |
+
+
+### 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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