End of training

README.md

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+---
+license: apache-2.0
+base_model: LaLegumbreArtificial/Fraunhofer_Classical
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: Fraunhofer_Classical_multiclass
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.761384335154827
+---
+
+<!-- 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. -->
+
+# Fraunhofer_Classical_multiclass
+
+This model is a fine-tuned version of [LaLegumbreArtificial/Fraunhofer_Classical](https://huggingface.co/LaLegumbreArtificial/Fraunhofer_Classical) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1740
+- Accuracy: 0.7614
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.0716        | 0.9976 | 208  | 0.8637          | 0.7752   |
+| 0.0478        | 2.0    | 417  | 0.7157          | 0.8339   |
+| 0.0408        | 2.9976 | 625  | 0.9172          | 0.8080   |
+| 0.031         | 4.0    | 834  | 0.9607          | 0.8104   |
+| 0.0258        | 4.9880 | 1040 | 1.1740          | 0.7614   |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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