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mozilla_dataset_processed_mel_spec_vit_1
ricardoSLabs/mozilla_dataset_processed_mel_spec_vit_1
mozilla_dataset_processed_mel_spec_vit_1 is a image classification model from ricardoSLabs. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Mar 31, 2025
- Updated
- Mar 31, 2025
- SHA
- c5125b2f
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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 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
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Mar 31, 2025
- Updated
- Mar 31, 2025