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+--------- config parameters ----------
+{
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+    },
+    "checkpoint_params": {
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+        "schema": null
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+        "load_opt_params": true,
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+        "metric_to_watch": "[email protected]",
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+        "silent_mode": true,
+        "mixed_precision": true,
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+        "dataset_statistics": false,
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+        "lr_schedule_function": null,
+        "train_metrics_list": [],
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+        "schema": {
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+            "collate_fn": "<super_gradients.training.utils.detection_utils.DetectionCollateFN object at 0x7f74b17472b0>"
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+            "requests 2.27.1",
+            "requests-oauthlib 1.3.1",
+            "requests-toolbelt 1.0.0",
+            "requirements-parser 0.5.0",
+            "rich 13.3.4",
+            "roboflow 1.0.8",
+            "rpy2 3.5.5",
+            "rsa 4.9",
+            "s3transfer 0.6.1",
+            "scikit-image 0.19.3",
+            "scikit-learn 1.2.2",
+            "scipy 1.10.1",
+            "scs 3.2.3",
+            "seaborn 0.12.2",
+            "setuptools 67.7.2",
+            "shapely 2.0.1",
+            "six 1.16.0",
+            "sklearn-pandas 2.2.0",
+            "smart-open 6.3.0",
+            "sniffio 1.3.0",
+            "snowballstemmer 2.2.0",
+            "sortedcontainers 2.4.0",
+            "soundfile 0.12.1",
+            "soupsieve 2.4.1",
+            "soxr 0.3.5",
+            "spacy 3.5.2",
+            "spacy-legacy 3.0.12",
+            "spacy-loggers 1.0.4",
+            "sphinx-rtd-theme 1.2.0",
+            "sphinxcontrib-applehelp 1.0.4",
+            "sphinxcontrib-devhelp 1.0.2",
+            "sphinxcontrib-htmlhelp 2.0.1",
+            "sphinxcontrib-jquery 4.1",
+            "sphinxcontrib-jsmath 1.0.1",
+            "sphinxcontrib-qthelp 1.0.3",
+            "sphinxcontrib-serializinghtml 1.1.5",
+            "sqlparse 0.4.4",
+            "srsly 2.4.6",
+            "statsmodels 0.13.5",
+            "stringcase 1.2.0",
+            "super-gradients 3.1.0",
+            "sympy 1.11.1",
+            "tables 3.8.0",
+            "tabulate 0.8.10",
+            "tblib 1.7.0",
+            "tenacity 8.2.2",
+            "tensorboard 2.12.2",
+            "tensorboard-data-server 0.7.0",
+            "tensorboard-plugin-wit 1.8.1",
+            "tensorflow 2.12.0",
+            "tensorflow-datasets 4.9.2",
+            "tensorflow-estimator 2.12.0",
+            "tensorflow-gcs-config 2.12.0",
+            "tensorflow-hub 0.13.0",
+            "tensorflow-io-gcs-filesystem 0.32.0",
+            "tensorflow-metadata 1.13.1",
+            "tensorflow-probability 0.19.0",
+            "tensorstore 0.1.36",
+            "termcolor 1.1.0",
+            "terminado 0.17.1",
+            "text-unidecode 1.3",
+            "textblob 0.17.1",
+            "tf-slim 1.1.0",
+            "thinc 8.1.9",
+            "threadpoolctl 3.1.0",
+            "tifffile 2023.4.12",
+            "tinycss2 1.2.1",
+            "toml 0.10.2",
+            "tomli 2.0.1",
+            "toolz 0.12.0",
+            "torch 1.13.1",
+            "torchaudio 2.0.1+cu118",
+            "torchdata 0.6.0",
+            "torchinfo 1.7.2",
+            "torchmetrics 0.8.0",
+            "torchsummary 1.5.1",
+            "torchtext 0.15.1",
+            "torchvision 0.14.1",
+            "tornado 6.3.1",
+            "tqdm 4.65.0",
+            "traitlets 5.7.1",
+            "treelib 1.6.1",
+            "triton 2.0.0",
+            "tweepy 4.13.0",
+            "typer 0.7.0",
+            "types-setuptools 67.7.0.2",
+            "typing-extensions 4.5.0",
+            "tzdata 2023.3",
+            "tzlocal 4.3",
+            "uritemplate 4.1.1",
+            "urllib3 1.26.15",
+            "vega-datasets 0.9.0",
+            "wasabi 1.1.1",
+            "wcwidth 0.2.6",
+            "webcolors 1.13",
+            "webencodings 0.5.1",
+            "websocket-client 1.5.1",
+            "wget 3.2",
+            "wheel 0.40.0",
+            "widgetsnbextension 3.6.4",
+            "wordcloud 1.8.2.2",
+            "wrapt 1.14.1",
+            "xarray 2022.12.0",
+            "xarray-einstats 0.5.1",
+            "xgboost 1.7.5",
+            "xlrd 2.0.1",
+            "yellowbrick 1.5",
+            "yfinance 0.2.18",
+            "youtube-dl 2021.12.17",
+            "zict 3.0.0",
+            "zipp 3.15.0",
+            "PyGObject 3.36.0",
+            "dbus-python 1.2.16",
+            "requests-unixsocket 0.2.0"
+        ]
+    }
+}
+------- config parameters end --------

my_first_yolonas_run/experiment_logs_May13_17_13_58.txt

@@ -0,0 +1,706 @@
+--------- config parameters ----------
+{
+    "arch_params": {
+        "schema": null
+    },
+    "checkpoint_params": {
+        "load_checkpoint": false,
+        "schema": null
+    },
+    "training_hyperparams": {
+        "lr_warmup_epochs": 3,
+        "lr_warmup_steps": 0,
+        "lr_cooldown_epochs": 0,
+        "warmup_initial_lr": 1e-06,
+        "cosine_final_lr_ratio": 0.1,
+        "optimizer": "Adam",
+        "optimizer_params": {
+            "weight_decay": 0.0001
+        },
+        "criterion_params": {},
+        "ema": true,
+        "batch_accumulate": 1,
+        "ema_params": {
+            "decay": 0.9,
+            "decay_type": "threshold"
+        },
+        "zero_weight_decay_on_bias_and_bn": true,
+        "load_opt_params": true,
+        "run_validation_freq": 1,
+        "save_model": true,
+        "metric_to_watch": "[email protected]",
+        "launch_tensorboard": false,
+        "tb_files_user_prompt": false,
+        "silent_mode": true,
+        "mixed_precision": true,
+        "tensorboard_port": null,
+        "save_ckpt_epoch_list": [],
+        "average_best_models": true,
+        "dataset_statistics": false,
+        "save_tensorboard_to_s3": false,
+        "lr_schedule_function": null,
+        "train_metrics_list": [],
+        "valid_metrics_list": [
+            "DetectionMetrics_050(\n  (post_prediction_callback): PPYoloEPostPredictionCallback()\n)"
+        ],
+        "greater_metric_to_watch_is_better": true,
+        "precise_bn": false,
+        "precise_bn_batch_size": null,
+        "seed": 42,
+        "lr_mode": "cosine",
+        "phase_callbacks": null,
+        "log_installed_packages": true,
+        "sg_logger": "base_sg_logger",
+        "sg_logger_params": {
+            "tb_files_user_prompt": false,
+            "project_name": "",
+            "launch_tensorboard": false,
+            "tensorboard_port": null,
+            "save_checkpoints_remote": false,
+            "save_tensorboard_remote": false,
+            "save_logs_remote": false
+        },
+        "warmup_mode": "linear_epoch_step",
+        "step_lr_update_freq": null,
+        "lr_updates": [],
+        "clip_grad_norm": null,
+        "pre_prediction_callback": null,
+        "ckpt_best_name": "ckpt_best.pth",
+        "enable_qat": false,
+        "resume": false,
+        "resume_path": null,
+        "ckpt_name": "ckpt_latest.pth",
+        "resume_strict_load": false,
+        "sync_bn": false,
+        "kill_ddp_pgroup_on_end": true,
+        "max_train_batches": null,
+        "max_valid_batches": null,
+        "schema": {
+            "type": "object",
+            "properties": {
+                "max_epochs": {
+                    "type": "number",
+                    "minimum": 1
+                },
+                "lr_decay_factor": {
+                    "type": "number",
+                    "minimum": 0,
+                    "maximum": 1
+                },
+                "lr_warmup_epochs": {
+                    "type": "number",
+                    "minimum": 0,
+                    "maximum": 10
+                },
+                "initial_lr": {
+                    "type": "number",
+                    "exclusiveMinimum": 0,
+                    "maximum": 10
+                }
+            },
+            "if": {
+                "properties": {
+                    "lr_mode": {
+                        "const": "step"
+                    }
+                }
+            },
+            "then": {
+                "required": [
+                    "lr_updates",
+                    "lr_decay_factor"
+                ]
+            },
+            "required": [
+                "max_epochs",
+                "lr_mode",
+                "initial_lr",
+                "loss"
+            ]
+        },
+        "initial_lr": 0.0005,
+        "max_epochs": 15,
+        "loss": "PPYoloELoss(\n  (static_assigner): ATSSAssigner()\n  (assigner): TaskAlignedAssigner()\n)"
+    },
+    "dataset_params": {
+        "train_dataset_params": {
+            "data_dir": "/content/New-pothole-detection-2",
+            "images_dir": "/content/New-pothole-detection-2/train/images",
+            "labels_dir": "/content/New-pothole-detection-2/train/labels",
+            "classes": [
+                "-1",
+                "0",
+                "Pothole",
+                "Potholes",
+                "bache",
+                "manhole",
+                "object",
+                "porthole",
+                "pothole",
+                "potholes"
+            ],
+            "input_dim": "[640, 640]",
+            "cache_dir": null,
+            "cache": false,
+            "transforms": "[{'DetectionMosaic': {'input_dim': [640, 640], 'prob': 1.0}}, {'DetectionRandomAffine': {'degrees': 10.0, 'translate': 0.1, 'scales': [0.1, 2], 'shear': 2.0, 'target_size': [640, 640], 'filter_box_candidates': True, 'wh_thr': 2, 'area_thr': 0.1, 'ar_thr': 20}}, {'DetectionMixup': {'input_dim': [640, 640], 'mixup_scale': [0.5, 1.5], 'prob': 1.0, 'flip_prob': 0.5}}, {'DetectionHSV': {'prob': 1.0, 'hgain': 5, 'sgain': 30, 'vgain': 30}}, {'DetectionHorizontalFlip': {'prob': 0.5}}, {'DetectionPaddedRescale': {'input_dim': [640, 640], 'max_targets': 120}}, {'DetectionTargetsFormatTransform': {'input_dim': [640, 640], 'output_format': 'LABEL_CXCYWH'}}]",
+            "class_inclusion_list": null,
+            "max_num_samples": null
+        },
+        "train_dataloader_params": {
+            "batch_size": 16,
+            "num_workers": 2,
+            "shuffle": true,
+            "drop_last": true,
+            "pin_memory": true,
+            "collate_fn": "<super_gradients.training.utils.detection_utils.DetectionCollateFN object at 0x7f74b1f19660>"
+        },
+        "valid_dataset_params": {
+            "data_dir": "/content/New-pothole-detection-2",
+            "images_dir": "/content/New-pothole-detection-2/valid/images",
+            "labels_dir": "/content/New-pothole-detection-2/valid/labels",
+            "classes": [
+                "-1",
+                "0",
+                "Pothole",
+                "Potholes",
+                "bache",
+                "manhole",
+                "object",
+                "porthole",
+                "pothole",
+                "potholes"
+            ],
+            "input_dim": "[640, 640]",
+            "cache_dir": null,
+            "cache": false,
+            "transforms": "[{'DetectionPaddedRescale': {'input_dim': [640, 640]}}, {'DetectionTargetsFormatTransform': {'max_targets': 50, 'input_dim': [640, 640], 'output_format': 'LABEL_CXCYWH'}}]",
+            "class_inclusion_list": null,
+            "max_num_samples": null
+        },
+        "valid_dataloader_params": {
+            "batch_size": 16,
+            "num_workers": 2,
+            "drop_last": false,
+            "pin_memory": true,
+            "collate_fn": "<super_gradients.training.utils.detection_utils.DetectionCollateFN object at 0x7f74b17472b0>"
+        },
+        "schema": null
+    },
+    "additional_log_items": {
+        "initial_LR": 0.0005,
+        "num_devices": 1,
+        "multi_gpu": "None",
+        "device_type": "Tesla T4",
+        "installed_packages": [
+            "Babel 2.12.1",
+            "CacheControl 0.12.11",
+            "Cython 0.29.34",
+            "Deprecated 1.2.13",
+            "Flask 2.2.4",
+            "GDAL 3.3.2",
+            "Jinja2 3.1.2",
+            "LunarCalendar 0.0.9",
+            "Markdown 3.4.3",
+            "MarkupSafe 2.1.2",
+            "Pillow 9.5.0",
+            "PyDrive 1.3.1",
+            "PyMeeus 0.5.12",
+            "PyOpenGL 3.1.6",
+            "PySocks 1.7.1",
+            "PyWavelets 1.4.1",
+            "PyYAML 6.0",
+            "Pygments 2.14.0",
+            "SQLAlchemy 2.0.10",
+            "Send2Trash 1.8.0",
+            "Sphinx 4.0.3",
+            "Werkzeug 2.3.0",
+            "absl-py 1.4.0",
+            "alabaster 0.7.13",
+            "albumentations 1.2.1",
+            "altair 4.2.2",
+            "antlr4-python3-runtime 4.9.3",
+            "anyio 3.6.2",
+            "appdirs 1.4.4",
+            "argon2-cffi 21.3.0",
+            "argon2-cffi-bindings 21.2.0",
+            "array-record 0.2.0",
+            "arviz 0.15.1",
+            "astropy 5.2.2",
+            "astunparse 1.6.3",
+            "attrs 23.1.0",
+            "audioread 3.0.0",
+            "autograd 1.5",
+            "backcall 0.2.0",
+            "beautifulsoup4 4.11.2",
+            "bleach 6.0.0",
+            "blis 0.7.9",
+            "blosc2 2.0.0",
+            "bokeh 2.4.3",
+            "boto3 1.26.133",
+            "botocore 1.29.133",
+            "branca 0.6.0",
+            "build 0.10.0",
+            "cached-property 1.5.2",
+            "cachetools 5.3.0",
+            "catalogue 2.0.8",
+            "certifi 2022.12.7",
+            "cffi 1.15.1",
+            "chardet 4.0.0",
+            "charset-normalizer 2.0.12",
+            "chex 0.1.7",
+            "click 8.1.3",
+            "cloudpickle 2.2.1",
+            "cmake 3.25.2",
+            "cmdstanpy 1.1.0",
+            "colorcet 3.0.1",
+            "coloredlogs 15.0.1",
+            "colorlover 0.3.0",
+            "community 1.0.0b1",
+            "confection 0.0.4",
+            "cons 0.4.5",
+            "contextlib2 0.6.0.post1",
+            "contourpy 1.0.7",
+            "convertdate 2.4.0",
+            "coverage 5.3.1",
+            "cryptography 40.0.2",
+            "cufflinks 0.17.3",
+            "cupy-cuda11x 11.0.0",
+            "cvxopt 1.3.0",
+            "cvxpy 1.3.1",
+            "cycler 0.10.0",
+            "cymem 2.0.7",
+            "dask 2022.12.1",
+            "datascience 0.17.6",
+            "db-dtypes 1.1.1",
+            "debugpy 1.6.6",
+            "decorator 4.4.2",
+            "defusedxml 0.7.1",
+            "distributed 2022.12.1",
+            "dlib 19.24.1",
+            "dm-tree 0.1.8",
+            "docutils 0.16",
+            "dopamine-rl 4.0.6",
+            "duckdb 0.7.1",
+            "earthengine-api 0.1.350",
+            "easydict 1.10",
+            "ecos 2.0.12",
+            "editdistance 0.6.2",
+            "einops 0.3.2",
+            "en-core-web-sm 3.5.0",
+            "entrypoints 0.4",
+            "ephem 4.1.4",
+            "et-xmlfile 1.1.0",
+            "etils 1.2.0",
+            "etuples 0.3.8",
+            "exceptiongroup 1.1.1",
+            "fastai 2.7.12",
+            "fastcore 1.5.29",
+            "fastdownload 0.0.7",
+            "fastjsonschema 2.16.3",
+            "fastprogress 1.0.3",
+            "fastrlock 0.8.1",
+            "filelock 3.12.0",
+            "firebase-admin 5.3.0",
+            "flatbuffers 23.3.3",
+            "flax 0.6.9",
+            "folium 0.14.0",
+            "fonttools 4.39.3",
+            "frozendict 2.3.7",
+            "fsspec 2023.4.0",
+            "future 0.18.3",
+            "gast 0.4.0",
+            "gdown 4.6.6",
+            "gensim 4.3.1",
+            "geographiclib 2.0",
+            "geopy 2.3.0",
+            "gin-config 0.5.0",
+            "glob2 0.7",
+            "google 2.0.3",
+            "google-api-core 2.11.0",
+            "google-api-python-client 2.84.0",
+            "google-auth 2.17.3",
+            "google-auth-httplib2 0.1.0",
+            "google-auth-oauthlib 1.0.0",
+            "google-cloud-bigquery 3.9.0",
+            "google-cloud-bigquery-storage 2.19.1",
+            "google-cloud-core 2.3.2",
+            "google-cloud-datastore 2.15.1",
+            "google-cloud-firestore 2.11.0",
+            "google-cloud-language 2.9.1",
+            "google-cloud-storage 2.8.0",
+            "google-cloud-translate 3.11.1",
+            "google-colab 1.0.0",
+            "google-crc32c 1.5.0",
+            "google-pasta 0.2.0",
+            "google-resumable-media 2.5.0",
+            "googleapis-common-protos 1.59.0",
+            "googledrivedownloader 0.4",
+            "graphviz 0.20.1",
+            "greenlet 2.0.2",
+            "grpcio 1.54.0",
+            "grpcio-status 1.48.2",
+            "gspread 3.4.2",
+            "gspread-dataframe 3.0.8",
+            "gym 0.25.2",
+            "gym-notices 0.0.8",
+            "h5netcdf 1.1.0",
+            "h5py 3.8.0",
+            "hijri-converter 2.3.1",
+            "holidays 0.23",
+            "holoviews 1.15.4",
+            "html5lib 1.1",
+            "httpimport 1.3.0",
+            "httplib2 0.21.0",
+            "humanfriendly 10.0",
+            "humanize 4.6.0",
+            "hydra-core 1.3.2",
+            "hyperopt 0.2.7",
+            "idna 2.10",
+            "imageio 2.25.1",
+            "imageio-ffmpeg 0.4.8",
+            "imagesize 1.4.1",
+            "imbalanced-learn 0.10.1",
+            "imgaug 0.4.0",
+            "importlib-resources 5.12.0",
+            "imutils 0.5.4",
+            "inflect 6.0.4",
+            "iniconfig 2.0.0",
+            "intel-openmp 2023.1.0",
+            "ipykernel 5.5.6",
+            "ipython 7.34.0",
+            "ipython-genutils 0.2.0",
+            "ipython-sql 0.4.1",
+            "ipywidgets 7.7.1",
+            "itsdangerous 2.1.2",
+            "jax 0.4.8",
+            "jaxlib 0.4.7+cuda11.cudnn86",
+            "jieba 0.42.1",
+            "jmespath 1.0.1",
+            "joblib 1.2.0",
+            "json-tricks 3.16.1",
+            "jsonpickle 3.0.1",
+            "jsonschema 4.3.3",
+            "jupyter-client 6.1.12",
+            "jupyter-console 6.1.0",
+            "jupyter-core 5.3.0",
+            "jupyter-server 1.24.0",
+            "jupyterlab-pygments 0.2.2",
+            "jupyterlab-widgets 3.0.7",
+            "kaggle 1.5.13",
+            "keras 2.12.0",
+            "kiwisolver 1.4.4",
+            "korean-lunar-calendar 0.3.1",
+            "langcodes 3.3.0",
+            "lazy-loader 0.2",
+            "libclang 16.0.0",
+            "librosa 0.10.0.post2",
+            "lightgbm 3.3.5",
+            "lit 16.0.3",
+            "llvmlite 0.39.1",
+            "locket 1.0.0",
+            "logical-unification 0.4.5",
+            "lxml 4.9.2",
+            "markdown-it-py 2.2.0",
+            "matplotlib 3.7.1",
+            "matplotlib-inline 0.1.6",
+            "matplotlib-venn 0.11.9",
+            "mdurl 0.1.2",
+            "miniKanren 1.0.3",
+            "missingno 0.5.2",
+            "mistune 0.8.4",
+            "mizani 0.8.1",
+            "mkl 2019.0",
+            "ml-dtypes 0.1.0",
+            "mlxtend 0.14.0",
+            "more-itertools 9.1.0",
+            "moviepy 1.0.3",
+            "mpmath 1.3.0",
+            "msgpack 1.0.5",
+            "multipledispatch 0.6.0",
+            "multitasking 0.0.11",
+            "murmurhash 1.0.9",
+            "music21 8.1.0",
+            "natsort 8.3.1",
+            "nbclient 0.7.4",
+            "nbconvert 6.5.4",
+            "nbformat 5.8.0",
+            "nest-asyncio 1.5.6",
+            "networkx 3.1",
+            "nibabel 3.0.2",
+            "nltk 3.8.1",
+            "notebook 6.4.8",
+            "numba 0.56.4",
+            "numexpr 2.8.4",
+            "numpy 1.22.4",
+            "nvidia-cublas-cu11 11.10.3.66",
+            "nvidia-cuda-nvrtc-cu11 11.7.99",
+            "nvidia-cuda-runtime-cu11 11.7.99",
+            "nvidia-cudnn-cu11 8.5.0.96",
+            "oauth2client 4.1.3",
+            "oauthlib 3.2.2",
+            "omegaconf 2.3.0",
+            "onnx 1.13.0",
+            "onnx-simplifier 0.4.28",
+            "onnxruntime 1.13.1",
+            "opencv-contrib-python 4.7.0.72",
+            "opencv-python 4.7.0.72",
+            "opencv-python-headless 4.7.0.72",
+            "openpyxl 3.0.10",
+            "opt-einsum 3.3.0",
+            "optax 0.1.5",
+            "orbax-checkpoint 0.2.1",
+            "osqp 0.6.2.post8",
+            "packaging 23.1",
+            "palettable 3.3.3",
+            "pandas 1.5.3",
+            "pandas-datareader 0.10.0",
+            "pandas-gbq 0.17.9",
+            "pandocfilters 1.5.0",
+            "panel 0.14.4",
+            "param 1.13.0",
+            "parso 0.8.3",
+            "partd 1.4.0",
+            "pathlib 1.0.1",
+            "pathy 0.10.1",
+            "patsy 0.5.3",
+            "pexpect 4.8.0",
+            "pickleshare 0.7.5",
+            "pip 23.1.2",
+            "pip-tools 6.13.0",
+            "platformdirs 3.3.0",
+            "plotly 5.13.1",
+            "plotnine 0.10.1",
+            "pluggy 1.0.0",
+            "polars 0.17.3",
+            "pooch 1.6.0",
+            "portpicker 1.3.9",
+            "prefetch-generator 1.0.3",
+            "preshed 3.0.8",
+            "prettytable 0.7.2",
+            "proglog 0.1.10",
+            "progressbar2 4.2.0",
+            "prometheus-client 0.16.0",
+            "promise 2.3",
+            "prompt-toolkit 3.0.38",
+            "prophet 1.1.2",
+            "proto-plus 1.22.2",
+            "protobuf 3.20.3",
+            "psutil 5.9.5",
+            "psycopg2 2.9.6",
+            "ptyprocess 0.7.0",
+            "py4j 0.10.9.7",
+            "pyDeprecate 0.3.2",
+            "py-cpuinfo 9.0.0",
+            "pyarrow 9.0.0",
+            "pyasn1 0.5.0",
+            "pyasn1-modules 0.3.0",
+            "pycocotools 2.0.4",
+            "pycparser 2.21",
+            "pyct 0.5.0",
+            "pydantic 1.10.7",
+            "pydata-google-auth 1.7.0",
+            "pydot 1.4.2",
+            "pydot-ng 2.0.0",
+            "pydotplus 2.0.2",
+            "pyerfa 2.0.0.3",
+            "pygame 2.3.0",
+            "pymc 5.1.2",
+            "pymystem3 0.2.0",
+            "pyparsing 2.4.7",
+            "pyproject-hooks 1.0.0",
+            "pyrsistent 0.19.3",
+            "pytensor 2.10.1",
+            "pytest 7.2.2",
+            "python-apt 0.0.0",
+            "python-dateutil 2.8.2",
+            "python-dotenv 1.0.0",
+            "python-louvain 0.16",
+            "python-slugify 8.0.1",
+            "python-utils 3.5.2",
+            "pytube 15.0.0",
+            "pytz 2022.7.1",
+            "pytz-deprecation-shim 0.1.0.post0",
+            "pyviz-comms 2.2.1",
+            "pyzmq 23.2.1",
+            "qdldl 0.1.7",
+            "qudida 0.0.4",
+            "rapidfuzz 3.0.0",
+            "regex 2022.10.31",
+            "requests 2.27.1",
+            "requests-oauthlib 1.3.1",
+            "requests-toolbelt 1.0.0",
+            "requirements-parser 0.5.0",
+            "rich 13.3.4",
+            "roboflow 1.0.8",
+            "rpy2 3.5.5",
+            "rsa 4.9",
+            "s3transfer 0.6.1",
+            "scikit-image 0.19.3",
+            "scikit-learn 1.2.2",
+            "scipy 1.10.1",
+            "scs 3.2.3",
+            "seaborn 0.12.2",
+            "setuptools 67.7.2",
+            "shapely 2.0.1",
+            "six 1.16.0",
+            "sklearn-pandas 2.2.0",
+            "smart-open 6.3.0",
+            "sniffio 1.3.0",
+            "snowballstemmer 2.2.0",
+            "sortedcontainers 2.4.0",
+            "soundfile 0.12.1",
+            "soupsieve 2.4.1",
+            "soxr 0.3.5",
+            "spacy 3.5.2",
+            "spacy-legacy 3.0.12",
+            "spacy-loggers 1.0.4",
+            "sphinx-rtd-theme 1.2.0",
+            "sphinxcontrib-applehelp 1.0.4",
+            "sphinxcontrib-devhelp 1.0.2",
+            "sphinxcontrib-htmlhelp 2.0.1",
+            "sphinxcontrib-jquery 4.1",
+            "sphinxcontrib-jsmath 1.0.1",
+            "sphinxcontrib-qthelp 1.0.3",
+            "sphinxcontrib-serializinghtml 1.1.5",
+            "sqlparse 0.4.4",
+            "srsly 2.4.6",
+            "statsmodels 0.13.5",
+            "stringcase 1.2.0",
+            "super-gradients 3.1.0",
+            "sympy 1.11.1",
+            "tables 3.8.0",
+            "tabulate 0.8.10",
+            "tblib 1.7.0",
+            "tenacity 8.2.2",
+            "tensorboard 2.12.2",
+            "tensorboard-data-server 0.7.0",
+            "tensorboard-plugin-wit 1.8.1",
+            "tensorflow 2.12.0",
+            "tensorflow-datasets 4.9.2",
+            "tensorflow-estimator 2.12.0",
+            "tensorflow-gcs-config 2.12.0",
+            "tensorflow-hub 0.13.0",
+            "tensorflow-io-gcs-filesystem 0.32.0",
+            "tensorflow-metadata 1.13.1",
+            "tensorflow-probability 0.19.0",
+            "tensorstore 0.1.36",
+            "termcolor 1.1.0",
+            "terminado 0.17.1",
+            "text-unidecode 1.3",
+            "textblob 0.17.1",
+            "tf-slim 1.1.0",
+            "thinc 8.1.9",
+            "threadpoolctl 3.1.0",
+            "tifffile 2023.4.12",
+            "tinycss2 1.2.1",
+            "toml 0.10.2",
+            "tomli 2.0.1",
+            "toolz 0.12.0",
+            "torch 1.13.1",
+            "torchaudio 2.0.1+cu118",
+            "torchdata 0.6.0",
+            "torchinfo 1.7.2",
+            "torchmetrics 0.8.0",
+            "torchsummary 1.5.1",
+            "torchtext 0.15.1",
+            "torchvision 0.14.1",
+            "tornado 6.3.1",
+            "tqdm 4.65.0",
+            "traitlets 5.7.1",
+            "treelib 1.6.1",
+            "triton 2.0.0",
+            "tweepy 4.13.0",
+            "typer 0.7.0",
+            "types-setuptools 67.7.0.2",
+            "typing-extensions 4.5.0",
+            "tzdata 2023.3",
+            "tzlocal 4.3",
+            "uritemplate 4.1.1",
+            "urllib3 1.26.15",
+            "vega-datasets 0.9.0",
+            "wasabi 1.1.1",
+            "wcwidth 0.2.6",
+            "webcolors 1.13",
+            "webencodings 0.5.1",
+            "websocket-client 1.5.1",
+            "wget 3.2",
+            "wheel 0.40.0",
+            "widgetsnbextension 3.6.4",
+            "wordcloud 1.8.2.2",
+            "wrapt 1.14.1",
+            "xarray 2022.12.0",
+            "xarray-einstats 0.5.1",
+            "xgboost 1.7.5",
+            "xlrd 2.0.1",
+            "yellowbrick 1.5",
+            "yfinance 0.2.18",
+            "youtube-dl 2021.12.17",
+            "zict 3.0.0",
+            "zipp 3.15.0",
+            "PyGObject 3.36.0",
+            "dbus-python 1.2.16",
+            "requests-unixsocket 0.2.0"
+        ]
+    }
+}
+------- config parameters end --------
+
+Epoch 0 (1/15)  - Train_PPYoloELoss/loss_cls: 1.6962181329727173	Train_PPYoloELoss/loss_iou: 0.2994749844074249	Train_PPYoloELoss/loss_dfl: 1.5699489116668701	Train_PPYoloELoss/loss: 3.2298800945281982	Valid_PPYoloELoss/loss_cls: 1.5147238969802856	Valid_PPYoloELoss/loss_iou: 0.27392876148223877	Valid_PPYoloELoss/loss_dfl: 1.4811557531356812	Valid_PPYoloELoss/loss: 2.9401230812072754	[email protected]: 0.04325180500745773	[email protected]: 0.38238680362701416	[email protected]: 0.089534230530262	[email protected]: 0.07771343737840652	Inference_Time: 87661.1875	
+
+Epoch 0 (1/15)  - LR/Param_group_0: 1e-06	LR/Param_group_1: 1e-06	
+
+Epoch 1 (2/15)  - Train_PPYoloELoss/loss_cls: 1.166463851928711	Train_PPYoloELoss/loss_iou: 0.2636335790157318	Train_PPYoloELoss/loss_dfl: 1.3941149711608887	Train_PPYoloELoss/loss: 2.52260684967041	Valid_PPYoloELoss/loss_cls: 1.2233375310897827	Valid_PPYoloELoss/loss_iou: 0.2455494999885559	Valid_PPYoloELoss/loss_dfl: 1.3523083925247192	Valid_PPYoloELoss/loss: 2.513366222381592	[email protected]: 0.015027979388833046	[email protected]: 0.8996546268463135	[email protected]: 0.4798499345779419	[email protected]: 0.029562147334218025	Inference_Time: 87491.5	
+
+Epoch 1 (2/15)  - LR/Param_group_0: 0.00016733333333333333	LR/Param_group_1: 0.00016733333333333333	
+
+Epoch 2 (3/15)  - Train_PPYoloELoss/loss_cls: 1.141836404800415	Train_PPYoloELoss/loss_iou: 0.2573237717151642	Train_PPYoloELoss/loss_dfl: 1.3711341619491577	Train_PPYoloELoss/loss: 2.4707140922546387	Valid_PPYoloELoss/loss_cls: 1.1793231964111328	Valid_PPYoloELoss/loss_iou: 0.24998177587985992	Valid_PPYoloELoss/loss_dfl: 1.3842113018035889	Valid_PPYoloELoss/loss: 2.4963839054107666	[email protected]: 0.016405094414949417	[email protected]: 0.8856484889984131	[email protected]: 0.42721670866012573	[email protected]: 0.0322134904563427	Inference_Time: 87581.796875	
+
+Epoch 2 (3/15)  - LR/Param_group_0: 0.0003336666666666667	LR/Param_group_1: 0.0003336666666666667	
+
+Epoch 3 (4/15)  - Train_PPYoloELoss/loss_cls: 1.150810718536377	Train_PPYoloELoss/loss_iou: 0.2577815055847168	Train_PPYoloELoss/loss_dfl: 1.3847109079360962	Train_PPYoloELoss/loss: 2.4876186847686768	Valid_PPYoloELoss/loss_cls: 1.2417112588882446	Valid_PPYoloELoss/loss_iou: 0.2563279867172241	Valid_PPYoloELoss/loss_dfl: 1.4326244592666626	Valid_PPYoloELoss/loss: 2.598844289779663	[email protected]: 0.017797669395804405	[email protected]: 0.8499616384506226	[email protected]: 0.395309716463089	[email protected]: 0.034865282475948334	Inference_Time: 86932.6484375	
+
+Epoch 3 (4/15)  - LR/Param_group_0: 0.0005	LR/Param_group_1: 0.0005	
+
+Epoch 4 (5/15)  - Train_PPYoloELoss/loss_cls: 1.1298094987869263	Train_PPYoloELoss/loss_iou: 0.24788755178451538	Train_PPYoloELoss/loss_dfl: 1.3363499641418457	Train_PPYoloELoss/loss: 2.417703628540039	Valid_PPYoloELoss/loss_cls: 1.1644823551177979	Valid_PPYoloELoss/loss_iou: 0.24936263263225555	Valid_PPYoloELoss/loss_dfl: 1.397640585899353	Valid_PPYoloELoss/loss: 2.486708879470825	[email protected]: 0.02170523814857006	[email protected]: 0.8601304888725281	[email protected]: 0.45845457911491394	[email protected]: 0.04234198480844498	Inference_Time: 86974.015625	
+
+Epoch 4 (5/15)  - LR/Param_group_0: 0.0004923767044943654	LR/Param_group_1: 0.0004923767044943654	
+
+Epoch 5 (6/15)  - Train_PPYoloELoss/loss_cls: 1.1231328248977661	Train_PPYoloELoss/loss_iou: 0.2438051998615265	Train_PPYoloELoss/loss_dfl: 1.3182282447814941	Train_PPYoloELoss/loss: 2.391761064529419	Valid_PPYoloELoss/loss_cls: 1.2028536796569824	Valid_PPYoloELoss/loss_iou: 0.24437254667282104	Valid_PPYoloELoss/loss_dfl: 1.377091407775879	Valid_PPYoloELoss/loss: 2.502331495285034	[email protected]: 0.017273498699069023	[email protected]: 0.8823868036270142	[email protected]: 0.48124265670776367	[email protected]: 0.03388369455933571	Inference_Time: 86847.265625	
+
+Epoch 5 (6/15)  - LR/Param_group_0: 0.0004699460572316118	LR/Param_group_1: 0.0004699460572316118	
+
+Epoch 6 (7/15)  - Train_PPYoloELoss/loss_cls: 1.1125056743621826	Train_PPYoloELoss/loss_iou: 0.24215054512023926	Train_PPYoloELoss/loss_dfl: 1.3027186393737793	Train_PPYoloELoss/loss: 2.3692400455474854	Valid_PPYoloELoss/loss_cls: 1.1844314336776733	Valid_PPYoloELoss/loss_iou: 0.24283626675605774	Valid_PPYoloELoss/loss_dfl: 1.3685951232910156	Valid_PPYoloELoss/loss: 2.4758198261260986	[email protected]: 0.01980043388903141	[email protected]: 0.8760552406311035	[email protected]: 0.45704999566078186	[email protected]: 0.0387255996465683	Inference_Time: 87195.390625	
+
+Epoch 6 (7/15)  - LR/Param_group_0: 0.00043423594998756126	LR/Param_group_1: 0.00043423594998756126	
+
+Epoch 7 (8/15)  - Train_PPYoloELoss/loss_cls: 1.0954060554504395	Train_PPYoloELoss/loss_iou: 0.23842182755470276	Train_PPYoloELoss/loss_dfl: 1.2814346551895142	Train_PPYoloELoss/loss: 2.3321774005889893	Valid_PPYoloELoss/loss_cls: 1.1549570560455322	Valid_PPYoloELoss/loss_iou: 0.2391127049922943	Valid_PPYoloELoss/loss_dfl: 1.36127507686615	Valid_PPYoloELoss/loss: 2.4333763122558594	[email protected]: 0.028354886919260025	[email protected]: 0.8434382081031799	[email protected]: 0.4446112811565399	[email protected]: 0.05486530065536499	Inference_Time: 87062.125	
+
+Epoch 7 (8/15)  - LR/Param_group_0: 0.00038767890664502167	LR/Param_group_1: 0.00038767890664502167	
+
+Epoch 8 (9/15)  - Train_PPYoloELoss/loss_cls: 1.094423532485962	Train_PPYoloELoss/loss_iou: 0.23351271450519562	Train_PPYoloELoss/loss_dfl: 1.263392448425293	Train_PPYoloELoss/loss: 2.309904098510742	Valid_PPYoloELoss/loss_cls: 1.0994166135787964	Valid_PPYoloELoss/loss_iou: 0.23664221167564392	Valid_PPYoloELoss/loss_dfl: 1.3241026401519775	Valid_PPYoloELoss/loss: 2.3530733585357666	[email protected]: 0.02528832107782364	[email protected]: 0.8906369805335999	[email protected]: 0.5475698709487915	[email protected]: 0.04918023943901062	Inference_Time: 87160.265625	
+
+Epoch 8 (9/15)  - LR/Param_group_0: 0.0003334463296047109	LR/Param_group_1: 0.0003334463296047109	
+
+Epoch 9 (10/15)  - Train_PPYoloELoss/loss_cls: 1.073317527770996	Train_PPYoloELoss/loss_iou: 0.2302723228931427	Train_PPYoloELoss/loss_dfl: 1.2447388172149658	Train_PPYoloELoss/loss: 2.271367311477661	Valid_PPYoloELoss/loss_cls: 1.1121559143066406	Valid_PPYoloELoss/loss_iou: 0.24138985574245453	Valid_PPYoloELoss/loss_dfl: 1.3346160650253296	Valid_PPYoloELoss/loss: 2.3829386234283447	[email protected]: 0.021185651421546936	[email protected]: 0.8948580026626587	[email protected]: 0.5400114059448242	[email protected]: 0.041391368955373764	Inference_Time: 86761.65625	
+
+Epoch 9 (10/15)  - LR/Param_group_0: 0.00027523246817188037	LR/Param_group_1: 0.00027523246817188037	
+
+Epoch 10 (11/15)  - Train_PPYoloELoss/loss_cls: 1.0707461833953857	Train_PPYoloELoss/loss_iou: 0.22916893661022186	Train_PPYoloELoss/loss_dfl: 1.2395823001861572	Train_PPYoloELoss/loss: 2.263460159301758	Valid_PPYoloELoss/loss_cls: 1.0663731098175049	Valid_PPYoloELoss/loss_iou: 0.23505419492721558	Valid_PPYoloELoss/loss_dfl: 1.3015613555908203	Valid_PPYoloELoss/loss: 2.3047895431518555	[email protected]: 0.026322683319449425	[email protected]: 0.9061780571937561	[email protected]: 0.5947054624557495	[email protected]: 0.05115928873419762	Inference_Time: 87799.5	
+
+Epoch 10 (11/15)  - LR/Param_group_0: 0.00021700277132370856	LR/Param_group_1: 0.00021700277132370856	
+
+Epoch 11 (12/15)  - Train_PPYoloELoss/loss_cls: 1.0621824264526367	Train_PPYoloELoss/loss_iou: 0.22597089409828186	Train_PPYoloELoss/loss_dfl: 1.2170137166976929	Train_PPYoloELoss/loss: 2.2356162071228027	Valid_PPYoloELoss/loss_cls: 1.1015101671218872	Valid_PPYoloELoss/loss_iou: 0.2394164651632309	Valid_PPYoloELoss/loss_dfl: 1.3316105604171753	Valid_PPYoloELoss/loss: 2.3658559322357178	[email protected]: 0.024049220606684685	[email protected]: 0.9052187204360962	[email protected]: 0.5670465230941772	[email protected]: 0.04685366526246071	Inference_Time: 86475.0703125	
+
+Epoch 11 (12/15)  - LR/Param_group_0: 0.00016272376672430553	LR/Param_group_1: 0.00016272376672430553	
+
+Epoch 12 (13/15)  - Train_PPYoloELoss/loss_cls: 1.049034833908081	Train_PPYoloELoss/loss_iou: 0.22144024074077606	Train_PPYoloELoss/loss_dfl: 1.1981967687606812	Train_PPYoloELoss/loss: 2.2017338275909424	Valid_PPYoloELoss/loss_cls: 1.0634980201721191	Valid_PPYoloELoss/loss_iou: 0.2294604629278183	Valid_PPYoloELoss/loss_dfl: 1.2745609283447266	Valid_PPYoloELoss/loss: 2.274430513381958	[email protected]: 0.027548959478735924	[email protected]: 0.9130851626396179	[email protected]: 0.595493733882904	[email protected]: 0.0534842312335968	Inference_Time: 87099.296875	
+
+Epoch 12 (13/15)  - LR/Param_group_0: 0.0001160928662610327	LR/Param_group_1: 0.0001160928662610327	
+
+Epoch 13 (14/15)  - Train_PPYoloELoss/loss_cls: 1.0481233596801758	Train_PPYoloELoss/loss_iou: 0.22079135477542877	Train_PPYoloELoss/loss_dfl: 1.1923013925552368	Train_PPYoloELoss/loss: 2.1962530612945557	Valid_PPYoloELoss/loss_cls: 1.0877412557601929	Valid_PPYoloELoss/loss_iou: 0.22792711853981018	Valid_PPYoloELoss/loss_dfl: 1.2632607221603394	Valid_PPYoloELoss/loss: 2.289189338684082	[email protected]: 0.021859185770154	[email protected]: 0.9265157580375671	[email protected]: 0.6112275719642639	[email protected]: 0.04271070286631584	Inference_Time: 87536.5234375	
+
+Epoch 13 (14/15)  - LR/Param_group_0: 8.028650338110862e-05	LR/Param_group_1: 8.028650338110862e-05	
+
+Epoch 14 (15/15)  - Train_PPYoloELoss/loss_cls: 1.0317202806472778	Train_PPYoloELoss/loss_iou: 0.2186751812696457	Train_PPYoloELoss/loss_dfl: 1.1811234951019287	Train_PPYoloELoss/loss: 2.168968439102173	Valid_PPYoloELoss/loss_cls: 1.054010272026062	Valid_PPYoloELoss/loss_iou: 0.23441554605960846	Valid_PPYoloELoss/loss_dfl: 1.27616548538208	Valid_PPYoloELoss/loss: 2.2781312465667725	[email protected]: 0.026609761640429497	[email protected]: 0.9163469076156616	[email protected]: 0.6239312887191772	[email protected]: 0.051717691123485565	Inference_Time: 87271.7265625	
+
+Epoch 14 (15/15)  - LR/Param_group_0: 5.774375877019629e-05	LR/Param_group_1: 5.774375877019629e-05	

my_first_yolonas_run/logs_May13_17_05_43.txt

@@ -0,0 +1,136 @@
+[2023-05-13 16:54:01] INFO - super_gradients.common.crash_handler.crash_tips_setup - Crash tips is enabled. You can set your environment variable to CRASH_HANDLER=FALSE to disable it
+[2023-05-13 16:54:06] DEBUG - pip._internal.vcs.versioncontrol - Registered VCS backend: bzr
+[2023-05-13 16:54:06] DEBUG - pip._internal.vcs.versioncontrol - Registered VCS backend: git
+[2023-05-13 16:54:06] DEBUG - pip._internal.vcs.versioncontrol - Registered VCS backend: hg
+[2023-05-13 16:54:06] DEBUG - pip._internal.vcs.versioncontrol - Registered VCS backend: svn
+[2023-05-13 16:54:06] DEBUG - super_gradients.common.sg_loggers.clearml_sg_logger - Failed to import clearml
+[2023-05-13 16:54:06] DEBUG - super_gradients.modules - Failed to import pytorch_quantization: cannot import name 'Bottleneck' from partially initialized module 'super_gradients.training.models.classification_models.resnet' (most likely due to a circular import) (/usr/local/lib/python3.10/dist-packages/super_gradients/training/models/classification_models/resnet.py)
+[2023-05-13 16:54:06] DEBUG - hydra.core.utils - Setting JobRuntime:name=UNKNOWN_NAME
+[2023-05-13 16:54:06] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 16:54:06] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 16:54:07] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 16:54:07] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 16:54:07] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 16:54:07] WARNING - super_gradients.training.utils.quantization - Failed to import pytorch_quantization
+[2023-05-13 16:54:07] WARNING - super_gradients.training.utils.quantization.calibrator - Failed to import pytorch_quantization
+[2023-05-13 16:54:07] WARNING - super_gradients.training.utils.quantization.export - Failed to import pytorch_quantization
+[2023-05-13 16:54:07] WARNING - super_gradients.training.utils.quantization.selective_quantization_utils - Failed to import pytorch_quantization
+[2023-05-13 16:54:07] DEBUG - super_gradients.training.qat_trainer.qat_trainer - Failed to import pytorch_quantization:
+[2023-05-13 16:54:07] DEBUG - super_gradients.training.qat_trainer.qat_trainer - name 'QuantizedMetadata' is not defined
+[2023-05-13 16:54:07] DEBUG - super_gradients.sanity_check.env_sanity_check - pyparsing==2.4.7 does not satisfy requirement pyparsing==2.4.5
+[2023-05-13 16:54:33] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): app.roboflow.com:443
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - https://app.roboflow.com:443 "GET /query/cliAuthToken/36509e31-f8df-4c6c-9182-357addecb9cd HTTP/1.1" 200 145
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "POST /?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 182
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "POST /?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 182
+[2023-05-13 16:54:34] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "GET /smartathon?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 3338
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "GET /smartathon/new-pothole-detection?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 7291
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "GET /smartathon/new-pothole-detection?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 7291
+[2023-05-13 16:54:35] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:36] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "GET /smartathon/new-pothole-detection/2?nocache=true&api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 4611
+[2023-05-13 16:54:36] DEBUG - urllib3.connectionpool - Starting new HTTPS connection (1): api.roboflow.com:443
+[2023-05-13 16:54:36] DEBUG - urllib3.connectionpool - https://api.roboflow.com:443 "GET /smartathon/new-pothole-detection/2/yolov5pytorch?api_key=2NdQm1ivtFCAYiOLVTwn HTTP/1.1" 200 3494
+[2023-05-13 17:01:06] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:01:08] WARNING - super_gradients.training.datasets.detection_datasets.detection_dataset - Found 1090 invalid bbox that were ignored. For more information, please set `show_all_warnings=True`.
+[2023-05-13 17:01:08] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:01:08] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:01:09] WARNING - super_gradients.training.datasets.detection_datasets.detection_dataset - Found 4 invalid bbox that were ignored. For more information, please set `show_all_warnings=True`.
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0.
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Italic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Oblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymReg.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansDisplay.ttf', name='DejaVu Sans Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFiveSymReg.ttf', name='STIXSizeFiveSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizOneSymBol.ttf', name='STIXSizeOneSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf', name='cmex10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerifDisplay.ttf', name='DejaVu Serif Display', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymReg.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymBol.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf', name='cmmi10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf', name='cmsy10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf', name='STIXNonUnicode', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymBol.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf', name='STIXNonUnicode', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf', name='STIXGeneral', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf', name='cmb10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizThreeSymReg.ttf', name='STIXSizeThreeSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf', name='cmtt10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf', name='cmss10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-Bold.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizFourSymBol.ttf', name='STIXSizeFourSym', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf', name='STIXGeneral', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono.ttf', name='DejaVu Sans Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Oblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=400, stretch='normal', size='scalable')) = 1.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSansMono-BoldOblique.ttf', name='DejaVu Sans Mono', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf', name='STIXGeneral', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf', name='cmr10', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 0.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXSizTwoSymReg.ttf', name='STIXSizeTwoSym', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf', name='STIXGeneral', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-BoldItalic.ttf', name='DejaVu Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSerif-Bold.ttf', name='DejaVu Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-BoldOblique.ttf', name='DejaVu Sans', style='oblique', variant='normal', weight=700, stretch='normal', size='scalable')) = 1.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans-Bold.ttf', name='DejaVu Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 0.33499999999999996
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Regular.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=400, stretch='condensed', size='scalable')) = 10.25
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Italic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-BoldItalic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=700, stretch='condensed', size='scalable')) = 11.535
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Bold.ttf', name='Liberation Sans Narrow', style='normal', variant='normal', weight=700, stretch='condensed', size='scalable')) = 10.535
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Bold.ttf', name='Liberation Mono', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Italic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Italic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=400, stretch='normal', size='scalable')) = 11.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-BoldItalic.ttf', name='Liberation Mono', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf', name='Liberation Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSansNarrow-Italic.ttf', name='Liberation Sans Narrow', style='italic', variant='normal', weight=400, stretch='condensed', size='scalable')) = 11.25
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-BoldItalic.ttf', name='Liberation Serif', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Bold.ttf', name='Liberation Serif', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-BoldItalic.ttf', name='Liberation Sans', style='italic', variant='normal', weight=700, stretch='normal', size='scalable')) = 11.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationMono-Regular.ttf', name='Liberation Mono', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSerif-Regular.ttf', name='Liberation Serif', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/humor-sans/Humor-Sans.ttf', name='Humor Sans', style='normal', variant='normal', weight=400, stretch='normal', size='scalable')) = 10.05
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: score(FontEntry(fname='/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf', name='Liberation Sans', style='normal', variant='normal', weight=700, stretch='normal', size='scalable')) = 10.335
+[2023-05-13 17:01:16] DEBUG - matplotlib.font_manager - findfont: Matching sans\-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=10.0 to DejaVu Sans ('/usr/local/lib/python3.10/dist-packages/matplotlib/mpl-data/fonts/ttf/DejaVuSans.ttf') with score of 0.050000.
+[2023-05-13 17:03:47] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:03:48] WARNING - super_gradients.training.datasets.detection_datasets.detection_dataset - Found 1090 invalid bbox that were ignored. For more information, please set `show_all_warnings=True`.
+[2023-05-13 17:03:48] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:03:49] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:03:49] WARNING - super_gradients.training.datasets.detection_datasets.detection_dataset - Found 4 invalid bbox that were ignored. For more information, please set `show_all_warnings=True`.
+[2023-05-13 17:04:34] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:04:36] INFO - super_gradients.training.utils.checkpoint_utils - License Notification: YOLO-NAS pre-trained weights are subjected to the specific license terms and conditions detailed in 
+https://github.com/Deci-AI/super-gradients/blob/master/LICENSE.YOLONAS.md
+By downloading the pre-trained weight files you agree to comply with these terms.
+[2023-05-13 17:05:36] INFO - super_gradients.training.sg_trainer.sg_trainer - Using EMA with params {'decay': 0.9, 'decay_type': 'threshold'}
+[2023-05-13 17:05:40] DEBUG - tensorflow - Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
+[2023-05-13 17:05:40] DEBUG - h5py._conv - Creating converter from 7 to 5
+[2023-05-13 17:05:40] DEBUG - h5py._conv - Creating converter from 5 to 7
+[2023-05-13 17:05:40] DEBUG - h5py._conv - Creating converter from 7 to 5
+[2023-05-13 17:05:40] DEBUG - h5py._conv - Creating converter from 5 to 7
+[2023-05-13 17:05:41] DEBUG - jaxlib.mlir._mlir_libs - Initializing MLIR with module: _site_initialize_0
+[2023-05-13 17:05:41] DEBUG - jaxlib.mlir._mlir_libs - Registering dialects from initializer <module 'jaxlib.mlir._mlir_libs._site_initialize_0' from '/usr/local/lib/python3.10/dist-packages/jaxlib/mlir/_mlir_libs/_site_initialize_0.so'>
+[2023-05-13 17:05:41] DEBUG - jax._src.path - etils.epath found. Using etils.epath for file I/O.
+[2023-05-13 17:05:42] INFO - numexpr.utils - NumExpr defaulting to 2 threads.
+[2023-05-13 17:05:49] INFO - super_gradients.training.utils.sg_trainer_utils - TRAINING PARAMETERS:
+    - Mode:                         Single GPU
+    - Number of GPUs:               1          (1 available on the machine)
+    - Dataset size:                 6086       (len(train_set))
+    - Batch size per GPU:           16         (batch_size)
+    - Batch Accumulate:             1          (batch_accumulate)
+    - Total batch size:             16         (num_gpus * batch_size)
+    - Effective Batch size:         16         (num_gpus * batch_size * batch_accumulate)
+    - Iterations per epoch:         380        (len(train_loader))
+    - Gradient updates per epoch:   380        (len(train_loader) / batch_accumulate)
+
+[2023-05-13 17:13:26] INFO - super_gradients.training.sg_trainer.sg_trainer - 
+[MODEL TRAINING EXECUTION HAS BEEN INTERRUPTED]... Please wait until SOFT-TERMINATION process finishes and saves all of the Model Checkpoints and log files before terminating...
+[2023-05-13 17:13:26] INFO - super_gradients.training.sg_trainer.sg_trainer - For HARD Termination - Stop the process again
+[2023-05-13 17:13:26] INFO - super_gradients.common.sg_loggers.base_sg_logger - [CLEANUP] - Successfully stopped system monitoring process
+[2023-05-13 17:13:27] DEBUG - hydra.core.utils - Setting JobRuntime:name=app
+[2023-05-13 17:13:57] INFO - super_gradients.training.sg_trainer.sg_trainer - Using EMA with params {'decay': 0.9, 'decay_type': 'threshold'}
+[2023-05-13 17:13:58] DEBUG - super_gradients.training.utils.sg_trainer_utils - "events.out.tfevents.1683998007.cf6772931124.3382.1" will not be deleted
+[2023-05-13 17:13:58] DEBUG - super_gradients.training.utils.sg_trainer_utils - "events.out.tfevents.1683997543.cf6772931124.3382.0" will not be deleted