| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224 |
| tags: |
| - image-classification |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: amns |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # amns |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the pcuenq/oxford-pets dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7099 |
| - Accuracy: 0.8871 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 16 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - 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 |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 31 | 1.3292 | 0.5574 | |
| | No log | 2.0 | 62 | 0.9371 | 0.8033 | |
| | No log | 3.0 | 93 | 0.7407 | 0.8852 | |
| | 1.2134 | 4.0 | 124 | 0.6463 | 0.9016 | |
| | 1.2134 | 5.0 | 155 | 0.6189 | 0.9016 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.46.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
|
|
