End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: WinKawaks/vit-tiny-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: mozilla_dataset_processed_mel_spec_vit_1
+  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: 0.94
+---
+
+<!-- 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. -->
+
+# mozilla_dataset_processed_mel_spec_vit_1
+
+This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4348
+- Accuracy: 0.94
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.7532        | 1.0   | 11   | 0.6034          | 0.6367   |
+| 0.4888        | 2.0   | 22   | 0.2861          | 0.9033   |
+| 0.2919        | 3.0   | 33   | 0.2482          | 0.92     |
+| 0.1771        | 4.0   | 44   | 0.2018          | 0.9233   |
+| 0.1011        | 5.0   | 55   | 0.2074          | 0.9233   |
+| 0.0563        | 6.0   | 66   | 0.2219          | 0.9367   |
+| 0.0251        | 7.0   | 77   | 0.2835          | 0.9333   |
+| 0.0041        | 8.0   | 88   | 0.3132          | 0.9367   |
+| 0.001         | 9.0   | 99   | 0.4014          | 0.94     |
+| 0.0           | 10.0  | 110  | 0.4260          | 0.9433   |
+| 0.0           | 11.0  | 121  | 0.4316          | 0.94     |
+| 0.0           | 12.0  | 132  | 0.4329          | 0.94     |
+| 0.0           | 13.0  | 143  | 0.4327          | 0.9433   |
+| 0.0           | 14.0  | 154  | 0.4334          | 0.94     |
+| 0.0           | 15.0  | 165  | 0.4339          | 0.94     |
+| 0.0           | 16.0  | 176  | 0.4340          | 0.94     |
+| 0.0           | 17.0  | 187  | 0.4344          | 0.94     |
+| 0.0           | 18.0  | 198  | 0.4346          | 0.94     |
+| 0.0           | 19.0  | 209  | 0.4347          | 0.94     |
+| 0.0           | 20.0  | 220  | 0.4348          | 0.94     |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.3.1
+- Tokenizers 0.21.0

model.safetensors

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