Model save

README.md

@@ -0,0 +1,95 @@
+---
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-pretraining-2024_04_02-atelectasis-classifier
+  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: 0.7644320297951583
+---
+
+<!-- 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. -->
+
+# vit-pretraining-2024_04_02-atelectasis-classifier
+
+This model was trained from scratch on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5020
+- Accuracy: 0.7644
+
+## 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-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.2
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.6304        | 1.0   | 537   | 0.6342          | 0.6709   |
+| 0.5931        | 2.0   | 1074  | 0.5669          | 0.7207   |
+| 0.5027        | 3.0   | 1611  | 0.5397          | 0.7393   |
+| 0.5659        | 4.0   | 2148  | 0.5341          | 0.7458   |
+| 0.5115        | 5.0   | 2685  | 0.5433          | 0.7346   |
+| 0.5108        | 6.0   | 3222  | 0.5454          | 0.7309   |
+| 0.5187        | 7.0   | 3759  | 0.5136          | 0.7621   |
+| 0.4435        | 8.0   | 4296  | 0.5057          | 0.7677   |
+| 0.583         | 9.0   | 4833  | 0.5042          | 0.7584   |
+| 0.5256        | 10.0  | 5370  | 0.5249          | 0.7495   |
+| 0.4818        | 11.0  | 5907  | 0.5212          | 0.7481   |
+| 0.5575        | 12.0  | 6444  | 0.5061          | 0.7481   |
+| 0.3572        | 13.0  | 6981  | 0.5042          | 0.7602   |
+| 0.489         | 14.0  | 7518  | 0.5004          | 0.7709   |
+| 0.4773        | 15.0  | 8055  | 0.5074          | 0.7700   |
+| 0.4577        | 16.0  | 8592  | 0.5054          | 0.7677   |
+| 0.4619        | 17.0  | 9129  | 0.5021          | 0.7686   |
+| 0.3865        | 18.0  | 9666  | 0.5074          | 0.7644   |
+| 0.4889        | 19.0  | 10203 | 0.5113          | 0.7598   |
+| 0.4637        | 20.0  | 10740 | 0.5020          | 0.7644   |
+
+
+### Framework versions
+
+- Transformers 4.39.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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