Image Classification
Transformers
Safetensors
English
siglip
SigLIP2
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Sneaker
Clog
Brogue
Instructions to use prithivMLmods/shoe-type-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/shoe-type-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/shoe-type-detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/shoe-type-detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/shoe-type-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-939/trainer_state.json from prithivMLmods/shoe-type-detection: direct link, hf CLI and curl.
- Browser
- Download file 1.83 kB
-
https://huggingface.co/prithivMLmods/shoe-type-detection/resolve/main/checkpoint-939/trainer_state.json
- Command line
-
hf download hf://prithivMLmods/shoe-type-detection/checkpoint-939/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/prithivMLmods/shoe-type-detection/resolve/main/checkpoint-939/trainer_state.json
1.83 kB
| { | |
| "best_global_step": 939, | |
| "best_metric": 0.3978084921836853, | |
| "best_model_checkpoint": "siglip2-finetune-full/checkpoint-939", | |
| "epoch": 3.0, | |
| "eval_steps": 500, | |
| "global_step": 939, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.6746, | |
| "eval_loss": 0.8624296188354492, | |
| "eval_model_preparation_time": 0.0023, | |
| "eval_runtime": 129.6436, | |
| "eval_samples_per_second": 77.135, | |
| "eval_steps_per_second": 9.642, | |
| "step": 313 | |
| }, | |
| { | |
| "epoch": 1.5974440894568689, | |
| "grad_norm": 10.701898574829102, | |
| "learning_rate": 0.00012512479201331117, | |
| "loss": 1.0067, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.7695, | |
| "eval_loss": 0.7205082774162292, | |
| "eval_model_preparation_time": 0.0023, | |
| "eval_runtime": 129.3402, | |
| "eval_samples_per_second": 77.315, | |
| "eval_steps_per_second": 9.664, | |
| "step": 626 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.8651, | |
| "eval_loss": 0.3978084921836853, | |
| "eval_model_preparation_time": 0.0023, | |
| "eval_runtime": 129.5132, | |
| "eval_samples_per_second": 77.212, | |
| "eval_steps_per_second": 9.652, | |
| "step": 939 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 1252, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 4, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 2.51272738289664e+18, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |