wandb

.gitignore

@@ -18,6 +18,9 @@ simclr_linear_probe/
 **/rng_state.pth
 **/training_args.bin
 
+# Weights & Biases
+wandb/
+
 # Python
 __pycache__/
 *.py[cod]

requirements.txt

@@ -1,60 +1,125 @@
-asttokens
-colorama
-comm
+accelerate==1.7.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.12.0
+aiosignal==1.3.2
+annotated-types==0.7.0
+asttokens==3.0.0
+async-timeout==5.0.1
+attrs==25.3.0
+certifi==2025.4.26
+charset-normalizer==3.4.2
+click==8.1.8
+colorama==0.4.6
+comm==0.2.2
 contourpy==1.3.0
 cycler==0.12.1
-debugpy
-decorator
-exceptiongroup
-executing
+datasets==3.6.0
+debugpy==1.8.14
+decorator==5.2.1
+dill==0.3.8
+docker-pycreds==0.4.0
+eval_type_backport==0.2.2
+exceptiongroup==1.3.0
+executing==2.2.0
+filelock==3.18.0
 fonttools==4.54.1
-importlib_metadata
-ipykernel
-ipython
-jedi
+frozenlist==1.6.0
+fsspec==2025.3.0
+gitdb==4.0.12
+GitPython==3.1.44
+hf-xet==1.1.2
+huggingface-hub==0.32.0
+idna==3.10
+importlib_metadata==8.7.0
+importlib_resources==6.5.2
+iniconfig==2.1.0
+ipykernel==6.29.5
+ipython==8.18.1
+jedi==0.19.2
+Jinja2==3.1.6
 joblib==1.4.2
-jupyter_client
-jupyter_core
+jupyter_client==8.6.3
+jupyter_core==5.7.2
 kiwisolver==1.4.7
+MarkupSafe==3.0.2
 matplotlib==3.9.2
-matplotlib-inline
-nest_asyncio
-numpy
-packaging
+matplotlib-inline==0.1.7
+mpmath==1.3.0
+multidict==6.4.4
+multiprocess==0.70.16
+nest-asyncio==1.6.0
+networkx==3.2.1
+numpy==2.0.2
+nvidia-cublas-cu12==12.6.4.1
+nvidia-cuda-cupti-cu12==12.6.80
+nvidia-cuda-nvrtc-cu12==12.6.77
+nvidia-cuda-runtime-cu12==12.6.77
+nvidia-cudnn-cu12==9.5.1.17
+nvidia-cufft-cu12==11.3.0.4
+nvidia-cufile-cu12==1.11.1.6
+nvidia-curand-cu12==10.3.7.77
+nvidia-cusolver-cu12==11.7.1.2
+nvidia-cusparse-cu12==12.5.4.2
+nvidia-cusparselt-cu12==0.6.3
+nvidia-ml-py==12.575.51
+nvidia-nccl-cu12==2.26.2
+nvidia-nvjitlink-cu12==12.6.85
+nvidia-nvtx-cu12==12.6.77
+packaging==25.0
 pandas==2.2.3
-parso
-pickleshare
+parso==0.8.4
+pexpect==4.9.0
+pickleshare==0.7.5
 pillow==11.0.0
-platformdirs
-prompt_toolkit
-psutil
-pure_eval
-Pygments
+platformdirs==4.3.8
+pluggy==1.6.0
+prompt_toolkit==3.0.51
+propcache==0.3.1
+protobuf==6.31.0
+psutil==7.0.0
+ptyprocess==0.7.0
+pure_eval==0.2.3
+pyarrow==20.0.0
+pydantic==2.11.5
+pydantic_core==2.33.2
+Pygments==2.19.1
+pynvml==12.0.0
 pyparsing==3.2.0
-python-dateutil
+pytest==8.3.5
+python-dateutil==2.9.0.post0
 pytz==2024.2
-pyzmq
+PyYAML==6.0.2
+pyzmq==26.4.0
+regex==2024.11.6
+requests==2.32.3
+safetensors==0.5.3
 scikit-learn==1.5.2
-scipy
-setuptools==75.1.0
-six
-stack-data
+scipy==1.13.1
+seaborn==0.13.2
+sentry-sdk==2.29.1
+setproctitle==1.3.6
+six==1.17.0
+smmap==5.0.2
+stack-data==0.6.3
+sympy==1.14.0
+thop==0.1.1.post2209072238
 threadpoolctl==3.5.0
-tornado
-traitlets
-typing_extensions
+timm==1.0.15
+tokenizers==0.21.1
+tomli==2.2.1
+torch==2.7.0
+torchvision==0.22.0
+tornado==6.5.1
+tqdm==4.67.1
+traitlets==5.14.3
+transformers==4.52.3
+triton==3.3.0
+typing-inspection==0.4.1
+typing_extensions==4.13.2
 tzdata==2024.2
-wcwidth
-wheel==0.44.0
-zipp
-# External/ML packages
-torch>=2.0.0
-torchvision>=0.15.0
-transformers>=4.36.0
-datasets>=2.14.0
-timm>=0.9.0
-seaborn>=0.12.0
-pynvml>=11.5.0
-thop>=0.1.1
-Pillow>=9.0.0  # included again for compatibility
-accelerate
+urllib3==2.4.0
+wandb==0.19.11
+wcwidth==0.2.13
+xxhash==3.5.0
+yarl==1.20.0
+zipp==3.21.0

results_metrics_finetune.json

@@ -1,18 +1,24 @@
 {
-    "simclr": {
-        "peak_memory_mb": 989.1875,
-        "flops_giga": 4.131698688,
-        "train_time_seconds": 417.5733857154846,
-        "eval_time_seconds": 25.519327640533447,
+    "vit": {
+        "model_name": "vit",
+        "model_type": "vit",
+        "peak_memory_mb": 3645.1875,
+        "flops_giga": 16.862863872,
+        "train_time_seconds": 454.5931091308594,
+        "eval_time_seconds": 33.34872579574585,
         "eval_metrics": {
-            "eval_loss": 0.6880730390548706,
-            "eval_accuracy": 0.6410256410256411,
-            "eval_f1": 0.6350267379679144,
-            "eval_auc": 0.6370808678500987,
-            "eval_runtime": 25.5184,
-            "eval_samples_per_second": 3.057,
-            "eval_steps_per_second": 0.196,
-            "epoch": 3.0
+            "eval_loss": 0.6044296026229858,
+            "eval_accuracy": 0.7435897435897436,
+            "eval_f1": 0.7420634920634921,
+            "eval_auc": 0.8060486522024982,
+            "eval_runtime": 33.3459,
+            "eval_samples_per_second": 2.339,
+            "eval_steps_per_second": 0.15,
+            "epoch": 3.0,
+            "model": "vit",
+            "phase": "finetune",
+            "gpu_memory_mb": 3645.1875,
+            "best_accuracy": 0.7435897435897436
         }
     }
 }

results_metrics_linear_probe.json

@@ -1,18 +1,25 @@
 {
-    "simclr": {
-        "peak_memory_mb": 1003.1875,
-        "flops_giga": 4.131698688,
-        "train_time_seconds": 128.30324125289917,
-        "eval_time_seconds": 25.598750591278076,
+    "vit": {
+        "model_name": "vit",
+        "model_type": "vit",
+        "phase": "linear_probe",
+        "peak_memory_mb": 3645.1875,
+        "flops_giga": 16.862863872,
+        "train_time_seconds": 186.49300956726074,
+        "eval_time_seconds": 40.83929514884949,
         "eval_metrics": {
-            "eval_loss": 0.6896047592163086,
-            "eval_accuracy": 0.5512820512820513,
-            "eval_f1": 0.49019607843137253,
-            "eval_auc": 0.5746219592373438,
-            "eval_runtime": 25.5978,
-            "eval_samples_per_second": 3.047,
-            "eval_steps_per_second": 0.195,
-            "epoch": 1.0
+            "eval_loss": 0.7638523578643799,
+            "eval_accuracy": 0.46153846153846156,
+            "eval_f1": 0.415,
+            "eval_auc": 0.38067061143984227,
+            "eval_runtime": 40.8364,
+            "eval_samples_per_second": 1.91,
+            "eval_steps_per_second": 0.122,
+            "epoch": 1.0,
+            "model": "vit",
+            "phase": "linear_probe",
+            "gpu_memory_mb": 1165.1875,
+            "best_accuracy": 0.46153846153846156
         }
     }
 }