| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: Plant_Classification_model_vit-base-patch16-224-in21k |
| 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. --> |
|
|
| # Plant_Classification_model_vit-base-patch16-224-in21k |
| |
| 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 None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.2650 |
| - Accuracy: 0.6667 |
| |
| ## 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-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 65 | 3.2430 | 0.0994 | |
| | No log | 2.0 | 130 | 3.1265 | 0.3060 | |
| | No log | 3.0 | 195 | 3.0009 | 0.3743 | |
| | No log | 4.0 | 260 | 2.8860 | 0.4133 | |
| | No log | 5.0 | 325 | 2.7848 | 0.4464 | |
| | No log | 6.0 | 390 | 2.6989 | 0.4951 | |
| | No log | 7.0 | 455 | 2.6229 | 0.5380 | |
| | 2.8794 | 8.0 | 520 | 2.5590 | 0.5653 | |
| | 2.8794 | 9.0 | 585 | 2.5042 | 0.5926 | |
| | 2.8794 | 10.0 | 650 | 2.4560 | 0.5984 | |
| | 2.8794 | 11.0 | 715 | 2.4151 | 0.6199 | |
| | 2.8794 | 12.0 | 780 | 2.3813 | 0.6316 | |
| | 2.8794 | 13.0 | 845 | 2.3516 | 0.6452 | |
| | 2.8794 | 14.0 | 910 | 2.3275 | 0.6511 | |
| | 2.8794 | 15.0 | 975 | 2.3079 | 0.6530 | |
| | 2.2983 | 16.0 | 1040 | 2.2919 | 0.6589 | |
| | 2.2983 | 17.0 | 1105 | 2.2801 | 0.6647 | |
| | 2.2983 | 18.0 | 1170 | 2.2717 | 0.6667 | |
| | 2.2983 | 19.0 | 1235 | 2.2667 | 0.6667 | |
| | 2.2983 | 20.0 | 1300 | 2.2650 | 0.6667 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.0.0 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
