Model save

README.md

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+---
+license: mit
+base_model: shi-labs/nat-mini-in1k-224
+tags:
+- generated_from_trainer
+datasets:
+- image_folder
+metrics:
+- accuracy
+- f1
+model-index:
+- name: nat-mini-in1k-224-finetuned-breakhis
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: image_folder
+      type: image_folder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9669421487603306
+    - name: F1
+      type: f1
+      value: 0.9612429172231991
+---
+
+<!-- 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. -->
+
+# nat-mini-in1k-224-finetuned-breakhis
+
+This model is a fine-tuned version of [shi-labs/nat-mini-in1k-224](https://huggingface.co/shi-labs/nat-mini-in1k-224) on the image_folder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0983
+- Accuracy: 0.9669
+- F1: 0.9612
+- Roc Auc: 0.9648
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Roc Auc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|
+| 0.3247        | 0.99  | 59   | 0.2084          | 0.9157   | 0.8968 | 0.8836  |
+| 0.1338        | 2.0   | 119  | 0.1686          | 0.9355   | 0.9266 | 0.9437  |
+| 0.1078        | 2.99  | 178  | 0.0986          | 0.9694   | 0.9636 | 0.9597  |
+| 0.0795        | 4.0   | 238  | 0.0957          | 0.9719   | 0.9668 | 0.9660  |
+| 0.0522        | 4.96  | 295  | 0.0983          | 0.9669   | 0.9612 | 0.9648  |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

runs/Mar18_09-23-06_4a1998b12619/events.out.tfevents.1710753825.4a1998b12619.129.0

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