Instructions to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat") model = AutoModelForImageClassification.from_pretrained("bryanzhou008/swin-tiny-patch4-window7-224-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.17777777777777778, | |
| "best_model_checkpoint": "swin-tiny-patch4-window7-224-finetuned-eurosat/checkpoint-6", | |
| "epoch": 2.4, | |
| "eval_steps": 500, | |
| "global_step": 6, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.8, | |
| "eval_accuracy": 0.07222222222222222, | |
| "eval_loss": 3.121551513671875, | |
| "eval_runtime": 8.8925, | |
| "eval_samples_per_second": 80.967, | |
| "eval_steps_per_second": 0.675, | |
| "step": 2 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.16944444444444445, | |
| "eval_loss": 3.0048022270202637, | |
| "eval_runtime": 4.0128, | |
| "eval_samples_per_second": 179.426, | |
| "eval_steps_per_second": 1.495, | |
| "step": 5 | |
| }, | |
| { | |
| "epoch": 2.4, | |
| "eval_accuracy": 0.17777777777777778, | |
| "eval_loss": 2.99086856842041, | |
| "eval_runtime": 3.3636, | |
| "eval_samples_per_second": 214.055, | |
| "eval_steps_per_second": 1.784, | |
| "step": 6 | |
| }, | |
| { | |
| "epoch": 2.4, | |
| "step": 6, | |
| "total_flos": 7.242513469341696e+16, | |
| "train_loss": 3.0775623321533203, | |
| "train_runtime": 60.6238, | |
| "train_samples_per_second": 59.383, | |
| "train_steps_per_second": 0.099 | |
| } | |
| ], | |
| "logging_steps": 10, | |
| "max_steps": 6, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 3, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 7.242513469341696e+16, | |
| "train_batch_size": 128, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |