| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: isl-model |
| 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: 0.7533380182712579 |
| --- |
| |
| <!-- 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. --> |
|
|
| # isl-model |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9812 |
| - Accuracy: 0.7533 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 2.6205 | 1.0 | 89 | 2.4275 | 0.5938 | |
| | 1.6582 | 2.0 | 178 | 1.6078 | 0.7063 | |
| | 1.3648 | 3.0 | 267 | 1.3754 | 0.7168 | |
| | 1.1069 | 4.0 | 356 | 1.2056 | 0.7323 | |
| | 1.1562 | 5.0 | 445 | 1.0958 | 0.7491 | |
| | 1.1048 | 6.0 | 534 | 1.0221 | 0.7583 | |
| | 0.9705 | 7.0 | 623 | 0.9831 | 0.7625 | |
| | 0.9059 | 8.0 | 712 | 1.0279 | 0.7386 | |
| | 0.9426 | 9.0 | 801 | 0.9511 | 0.7632 | |
| | 0.8951 | 10.0 | 890 | 0.9812 | 0.7533 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.1 |
| - Pytorch 2.0.0+cu118 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
|
|
