Instructions to use DeepLearner101/CIFARSelectedSubsetBasedModel-Training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/CIFARSelectedSubsetBasedModel-Training with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/CIFARSelectedSubsetBasedModel-Training") 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("DeepLearner101/CIFARSelectedSubsetBasedModel-Training") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/CIFARSelectedSubsetBasedModel-Training") - Notebooks
- Google Colab
- Kaggle
Commit ·
c160deb
1
Parent(s): aa55671
Upload hyperparameters_tuning_results.csv with huggingface_hub
Browse files
hyperparameters_tuning_results.csv
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
date,timestamp,pid,hostname,node_ip,config/lr,config/weight_decay,config/dropout_rate,config/l1_factor,config/epochs,config/epsilon_range,config/step_size,config/gamma,config/early_stopping_tolerance,config/training_batch_size,config/validation_batch_size
|
| 2 |
-
2023-12-29_15-
|
| 3 |
-
|
| 4 |
,,,,,,,,,,,,,,,
|
| 5 |
,,,,,,,,,,,,,,,
|
| 6 |
,,,,,,,,,,,,,,,
|
|
|
|
| 1 |
date,timestamp,pid,hostname,node_ip,config/lr,config/weight_decay,config/dropout_rate,config/l1_factor,config/epochs,config/epsilon_range,config/step_size,config/gamma,config/early_stopping_tolerance,config/training_batch_size,config/validation_batch_size
|
| 2 |
+
2023-12-29_15-44-19,1703864659.0,3178.0,ef8dc7a348d9,172.28.0.12,0.000838298770890843,7.765053807979055e-05,0.39026342718993856,6.094095283712306e-06,12.0,"(0.001, 0.007, 0.002)",5.0,0.3,5.0,128.0,32.0
|
| 3 |
+
,,,,,,,,,,,,,,,
|
| 4 |
,,,,,,,,,,,,,,,
|
| 5 |
,,,,,,,,,,,,,,,
|
| 6 |
,,,,,,,,,,,,,,,
|