| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: lens-1 |
| | 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. --> |
| |
|
| | # lens-1 |
| |
|
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1819 |
| | - Accuracy: 0.57 |
| |
|
| | ## 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: 1e-06 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.5087 | 1.0 | 200 | 1.1273 | 0.545 | |
| | | 0.5636 | 2.0 | 400 | 1.1752 | 0.545 | |
| | | 0.5356 | 3.0 | 600 | 1.2058 | 0.52 | |
| | | 0.6525 | 4.0 | 800 | 1.0978 | 0.545 | |
| | | 0.4262 | 5.0 | 1000 | 1.1396 | 0.55 | |
| | | 0.5066 | 6.0 | 1200 | 1.1730 | 0.53 | |
| | | 0.3765 | 7.0 | 1400 | 1.1041 | 0.585 | |
| | | 0.3869 | 8.0 | 1600 | 1.2183 | 0.525 | |
| | | 0.4331 | 9.0 | 1800 | 1.1815 | 0.535 | |
| | | 0.4646 | 10.0 | 2000 | 1.1397 | 0.57 | |
| | | 0.6802 | 11.0 | 2200 | 1.1624 | 0.525 | |
| | | 0.679 | 12.0 | 2400 | 1.1541 | 0.52 | |
| | | 0.6286 | 13.0 | 2600 | 1.1933 | 0.52 | |
| | | 0.663 | 14.0 | 2800 | 1.2535 | 0.5 | |
| | | 0.4078 | 15.0 | 3000 | 1.2326 | 0.495 | |
| | | 0.6179 | 16.0 | 3200 | 1.1901 | 0.52 | |
| | | 0.4192 | 17.0 | 3400 | 1.2329 | 0.525 | |
| | | 0.3685 | 18.0 | 3600 | 1.2212 | 0.505 | |
| | | 0.4928 | 19.0 | 3800 | 1.1887 | 0.555 | |
| | | 0.5752 | 20.0 | 4000 | 1.1819 | 0.57 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.35.0 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.14.6 |
| | - Tokenizers 0.14.1 |
| | |
