Image Classification
Transformers
Safetensors
English
siglip
Cat
Dog
Classification
SigLIP2
Vision-encoder
Instructions to use prithivMLmods/PussyCat-vs-Doggie-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/PussyCat-vs-Doggie-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/PussyCat-vs-Doggie-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/PussyCat-vs-Doggie-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/PussyCat-vs-Doggie-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-1564/trainer_state.json from prithivMLmods/PussyCat-vs-Doggie-SigLIP2: direct link, hf CLI and curl.
- Browser
- Download file 1.89 kB
-
https://huggingface.co/prithivMLmods/PussyCat-vs-Doggie-SigLIP2/resolve/main/checkpoint-1564/trainer_state.json
- Command line
-
hf download hf://prithivMLmods/PussyCat-vs-Doggie-SigLIP2/checkpoint-1564/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/prithivMLmods/PussyCat-vs-Doggie-SigLIP2/resolve/main/checkpoint-1564/trainer_state.json
1.89 kB
| { | |
| "best_global_step": 1564, | |
| "best_metric": 0.3568730354309082, | |
| "best_model_checkpoint": "siglip2-finetune-full/checkpoint-1564", | |
| "epoch": 2.0, | |
| "eval_steps": 500, | |
| "global_step": 1564, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.639386189258312, | |
| "grad_norm": 4.334684371948242, | |
| "learning_rate": 0.000160801393728223, | |
| "loss": 0.642, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.74792, | |
| "eval_loss": 0.5220636129379272, | |
| "eval_model_preparation_time": 0.0024, | |
| "eval_runtime": 325.9979, | |
| "eval_samples_per_second": 76.688, | |
| "eval_steps_per_second": 9.586, | |
| "step": 782 | |
| }, | |
| { | |
| "epoch": 1.278772378516624, | |
| "grad_norm": 6.341824054718018, | |
| "learning_rate": 0.00011724738675958189, | |
| "loss": 0.554, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 1.918158567774936, | |
| "grad_norm": 3.435889482498169, | |
| "learning_rate": 7.369337979094078e-05, | |
| "loss": 0.4517, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.8422, | |
| "eval_loss": 0.3568730354309082, | |
| "eval_model_preparation_time": 0.0024, | |
| "eval_runtime": 325.7227, | |
| "eval_samples_per_second": 76.752, | |
| "eval_steps_per_second": 9.594, | |
| "step": 1564 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 2346, | |
| "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": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 4.1877747910656e+18, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |