Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: 2D_hgg_lgg_classification
+  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: 0.796875
+---
+
+<!-- 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. -->
+
+# 2D_hgg_lgg_classification
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5088
+- Accuracy: 0.7969
+
+## 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: 30
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.6381        | 0.9655  | 7    | 0.5358          | 0.7812   |
+| 0.5538        | 1.9310  | 14   | 0.5186          | 0.7812   |
+| 0.5046        | 2.8966  | 21   | 0.5115          | 0.7812   |
+| 0.4162        | 4.0     | 29   | 0.4877          | 0.7344   |
+| 0.4193        | 4.9655  | 36   | 0.4512          | 0.8047   |
+| 0.3897        | 5.9310  | 43   | 0.4098          | 0.7969   |
+| 0.3605        | 6.8966  | 50   | 0.3844          | 0.7891   |
+| 0.3091        | 8.0     | 58   | 0.3819          | 0.8125   |
+| 0.3058        | 8.9655  | 65   | 0.3914          | 0.7969   |
+| 0.3363        | 9.9310  | 72   | 0.4284          | 0.8125   |
+| 0.3077        | 10.8966 | 79   | 0.3902          | 0.8047   |
+| 0.2812        | 12.0    | 87   | 0.3666          | 0.8047   |
+| 0.2905        | 12.9655 | 94   | 0.3778          | 0.7969   |
+| 0.2518        | 13.9310 | 101  | 0.3879          | 0.7969   |
+| 0.2326        | 14.8966 | 108  | 0.4155          | 0.7891   |
+| 0.2084        | 16.0    | 116  | 0.4968          | 0.7812   |
+| 0.194         | 16.9655 | 123  | 0.4423          | 0.7969   |
+| 0.1994        | 17.9310 | 130  | 0.4206          | 0.7969   |
+| 0.1999        | 18.8966 | 137  | 0.4231          | 0.7734   |
+| 0.1818        | 20.0    | 145  | 0.4296          | 0.7891   |
+| 0.1941        | 20.9655 | 152  | 0.4669          | 0.7734   |
+| 0.1908        | 21.9310 | 159  | 0.5078          | 0.7891   |
+| 0.2101        | 22.8966 | 166  | 0.4540          | 0.7969   |
+| 0.1483        | 24.0    | 174  | 0.4606          | 0.8125   |
+| 0.181         | 24.9655 | 181  | 0.4973          | 0.7969   |
+| 0.1744        | 25.9310 | 188  | 0.4852          | 0.8125   |
+| 0.1724        | 26.8966 | 195  | 0.5032          | 0.8047   |
+| 0.1399        | 28.0    | 203  | 0.5112          | 0.8047   |
+| 0.1598        | 28.9655 | 210  | 0.5088          | 0.7969   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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