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The correct CUDA version is installed, compatible with both your GPU and the libraries you're using. If using Docker, make sure the image supports your GPU’s CUDA version. Try downgrading...

Pre-training Loss:In BEATS, cross-entropy loss starts around 3.0–4.0 (BEATSiter1) and plateaus near 1.5–2.5 (BEATSiter2), aligning with trends in masked audio models like HuBERT. Loss curves are not public but likely...

CUDA Version Mismatch: PyTorch in your setup supports CUDA up to 12.4, but the workstation has CUDA 12.6 installed. This mismatch causes the RuntimeError: NVML_SUCCESS == DriverAPI::get()->nvmlInit_v2_() issue, as PyTorch...

modify the requirements.txt to explicitly install the GPU-compatible version of TensorFlow by specifying tensorflow-gpu or tensorflow==2.x+nv instead of tensorflow-cpu. Ensure your Dockerfile uses a GPU-enabled base image, such as nvidia/cuda:12.2.0-cudnn8-runtime-ubuntu20.04,...