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run_q4_output.log
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/home/m25csa028/miniconda3/lib/python3.13/site-packages/torch/cuda/__init__.py:180: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 12040). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:119.)
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return torch._C._cuda_getDeviceCount() > 0
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============================================================
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Q4: ECAPA-TDNN Speaker Verification — Full Pipeline
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============================================================
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[TASK 1] Loading pre-trained ECAPA-TDNN model...
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Baseline GFLOPs (FP32): 11.3189
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Loading SUPERB SI test split (streaming)...
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Evaluating Baseline Accuracy (cosine-sim nearest neighbour)...
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Baseline Top-1 Identification Accuracy: 100.00%
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[TASK 2] Applying Post-Training Quantization (INT8 Dynamic)...
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PTQ (INT8) Effective GFLOPs: 2.8297
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GFLOPs Reduction: 8.4892 (75.0%)
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[TASK 3] Evaluating PTQ model on test set...
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PTQ Accuracy: 100.00%
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Accuracy Change vs Baseline: +0.00% (maintained/increased)
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[TASK 4] Running Optuna QAT hyperparameter search (4 trials)...
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Trial 0: lr=1.33e-04, wd=7.11e-04, bs=8 → Adapter Acc=2.50%
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Trial 1: lr=2.94e-05, wd=1.49e-06, bs=8 → Adapter Acc=0.42%
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Trial 2: lr=1.15e-05, wd=8.12e-04, bs=8 → Adapter Acc=0.42%
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Trial 3: lr=3.55e-05, wd=8.18e-06, bs=8 → Adapter Acc=0.00%
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Best Hyperparameters: {'lr': 0.0001329291894316216, 'weight_decay': 0.0007114476009343421, 'batch_size': 8}
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Best QAT Adapter Accuracy (val-trained): 2.50%
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QAT Inference GFLOPs: 2.8297
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[TASK 5] Final Trade-off Analysis...
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Baseline Accuracy: 100.00%
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Final QAT Model Accuracy: 100.00%
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Total Perf Difference: +0.00% (improvement)
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GFLOPs Saved permanently: 8.4892 GFLOPs
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Results saved to q4_results.json
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============================================================
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ANSWERS FOR SUBMISSION BLANKS:
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============================================================
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Task 1: Baseline Accuracy = 100.00%
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Task 1: Baseline GFLOPs = 11.3189 GFLOPs
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Task 2: PTQ (INT8) GFLOPs = 2.8297 GFLOPs
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Task 2: GFLOPs Impact = 8.4892 GFLOPs reduction (75.0%)
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Task 3: PTQ Accuracy = 100.00% (Accuracy maintained/increased)
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Task 4: Best Hyperparams = lr=1.33e-04, weight_decay=7.11e-04, batch_size=8
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Task 4: Best QAT Accuracy = 2.50%
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Task 4: QAT GFLOPs = 2.8297 GFLOPs
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Task 5: Total Perf Diff = 0.00% absolute Accuracy difference
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Task 5: GFLOPs Saved = 8.4892 GFLOPs permanently saved
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============================================================
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'[Errno 9] Bad file descriptor' thrown while requesting GET https://huggingface.co/datasets/s3prl/superb/resolve/4b5ccb1d4776ce2af83f86a175137663835f0b1c/si/validation-00000-of-00001.parquet
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Retrying in 1s [Retry 1/5].
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