Model save

README.md

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+---
+license: apache-2.0
+base_model: Visual-Attention-Network/van-tiny
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- recall
+- precision
+model-index:
+- name: teacher-status-van-tiny-256-1-2
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9664218258132214
+    - name: Recall
+      type: recall
+      value: 0.9737704918032787
+    - name: Precision
+      type: precision
+      value: 0.9737704918032787
+---
+
+<!-- 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. -->
+
+# teacher-status-van-tiny-256-1-2
+
+This model is a fine-tuned version of [Visual-Attention-Network/van-tiny](https://huggingface.co/Visual-Attention-Network/van-tiny) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0858
+- Accuracy: 0.9664
+- F1 Score: 0.9738
+- Recall: 0.9738
+- Precision: 0.9738
+
+## 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: 128
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
+| 0.6722        | 0.99  | 33   | 0.6499          | 0.6401   | 0.7806   | 1.0    | 0.6401    |
+| 0.5431        | 2.0   | 67   | 0.4164          | 0.7817   | 0.8531   | 0.9902 | 0.7494    |
+| 0.393         | 2.99  | 100  | 0.2833          | 0.8877   | 0.9078   | 0.8639 | 0.9564    |
+| 0.354         | 4.0   | 134  | 0.1930          | 0.9276   | 0.9436   | 0.9459 | 0.9413    |
+| 0.3007        | 4.99  | 167  | 0.1585          | 0.9370   | 0.9511   | 0.9557 | 0.9464    |
+| 0.2898        | 6.0   | 201  | 0.1445          | 0.9465   | 0.9581   | 0.9557 | 0.9605    |
+| 0.2824        | 6.99  | 234  | 0.1353          | 0.9465   | 0.9580   | 0.9525 | 0.9635    |
+| 0.2763        | 8.0   | 268  | 0.1359          | 0.9486   | 0.9603   | 0.9721 | 0.9488    |
+| 0.2473        | 8.99  | 301  | 0.1213          | 0.9570   | 0.9664   | 0.9672 | 0.9656    |
+| 0.2598        | 10.0  | 335  | 0.1091          | 0.9570   | 0.9665   | 0.9705 | 0.9626    |
+| 0.2476        | 10.99 | 368  | 0.1041          | 0.9633   | 0.9714   | 0.9754 | 0.9675    |
+| 0.2376        | 12.0  | 402  | 0.0997          | 0.9601   | 0.9686   | 0.9623 | 0.9751    |
+| 0.2402        | 12.99 | 435  | 0.0972          | 0.9622   | 0.9704   | 0.9672 | 0.9736    |
+| 0.2324        | 14.0  | 469  | 0.0950          | 0.9664   | 0.9739   | 0.9803 | 0.9676    |
+| 0.2256        | 14.99 | 502  | 0.0909          | 0.9706   | 0.9770   | 0.9754 | 0.9786    |
+| 0.21          | 16.0  | 536  | 0.0922          | 0.9622   | 0.9703   | 0.9656 | 0.9752    |
+| 0.217         | 16.99 | 569  | 0.0933          | 0.9612   | 0.9695   | 0.9656 | 0.9736    |
+| 0.2092        | 18.0  | 603  | 0.0891          | 0.9664   | 0.9738   | 0.9754 | 0.9722    |
+| 0.2063        | 18.99 | 636  | 0.0913          | 0.9654   | 0.9730   | 0.9738 | 0.9722    |
+| 0.2217        | 20.0  | 670  | 0.0917          | 0.9643   | 0.9720   | 0.9672 | 0.9768    |
+| 0.1952        | 20.99 | 703  | 0.0859          | 0.9717   | 0.9778   | 0.9754 | 0.9802    |
+| 0.2068        | 22.0  | 737  | 0.0907          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
+| 0.1914        | 22.99 | 770  | 0.0847          | 0.9696   | 0.9763   | 0.9787 | 0.9739    |
+| 0.1961        | 24.0  | 804  | 0.0870          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
+| 0.1911        | 24.99 | 837  | 0.0884          | 0.9664   | 0.9739   | 0.9770 | 0.9707    |
+| 0.1961        | 26.0  | 871  | 0.0870          | 0.9685   | 0.9754   | 0.9738 | 0.9770    |
+| 0.1978        | 26.99 | 904  | 0.0871          | 0.9685   | 0.9754   | 0.9754 | 0.9754    |
+| 0.1854        | 28.0  | 938  | 0.0858          | 0.9685   | 0.9755   | 0.9770 | 0.9739    |
+| 0.1733        | 28.99 | 971  | 0.0860          | 0.9685   | 0.9754   | 0.9738 | 0.9770    |
+| 0.1762        | 29.55 | 990  | 0.0858          | 0.9664   | 0.9738   | 0.9738 | 0.9738    |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

model.safetensors

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