| | --- |
| | 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 |
| |
|
