(fairseq) dilip@dilip-Komplett-PC:/media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/scripts/finetuning$ bash start_finetuning.sh
Directory to code is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation
Config path is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/config/finetuning/
Data path is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/data/finetuning
Checkpoint will be saved at: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/checkpoints/finetuning
Logs will be saved at: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/logs/finetuning
** Update frequency is: -24/usr/local/lib/python3.8/dist-packages/torch/cuda/init.py:143: UserWarning:
NVIDIA GeForce RTX 3090 with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the NVIDIA GeForce RTX 3090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
(fairseq) dilip@dilip-Komplett-PC:/media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/scripts/finetuning$ bash start_finetuning.sh Directory to code is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation Config path is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/config/finetuning/ Data path is: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/data/finetuning Checkpoint will be saved at: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/checkpoints/finetuning Logs will be saved at: /media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/logs/finetuning ** Update frequency is: -24/usr/local/lib/python3.8/dist-packages/torch/cuda/init.py:143: UserWarning: NVIDIA GeForce RTX 3090 with CUDA capability sm_86 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70. If you want to use the NVIDIA GeForce RTX 3090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name)) [2024-04-23 21:22:46,943][fairseq_cli.train][INFO] - {'_name': None, 'common': {'_name': None, 'no_progress_bar': False, 'log_interval': 1, 'log_format': 'json', 'log_file': None, 'aim_repo': None, 'aim_run_hash': None, 'tensorboard_logdir': '/media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/logs/finetuning/tensorboard', 'wandb_project': None, 'azureml_logging': False, 'seed': 1, 'cpu': False, 'tpu': False, 'bf16': False, 'memory_efficient_bf16': False, 'fp16': True, 'memory_efficient_fp16': False, 'fp16_no_flatten_grads': False, 'fp16_init_scale': 128, 'fp16_scale_window': None, 'fp16_scale_tolerance': 0.0, 'on_cpu_convert_precision': False, 'min_loss_scale': 0.0001, 'threshold_loss_scale': None, 'amp': False, 'amp_batch_retries': 2, 'amp_init_scale': 128, 'amp_scale_window': None, 'user_dir': None, 'empty_cache_freq': 0, 'all_gather_list_size': 16384, 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'sampling': False, 'sampling_topk': -1, 'sampling_topp': -1.0, 'constraints': None, 'temperature': 1.0, 'diverse_beam_groups': -1, 'diverse_beam_strength': 0.5, 'diversity_rate': -1.0, 'print_alignment': None, 'print_step': False, 'lm_path': None, 'lm_weight': 0.0, 'iter_decode_eos_penalty': 0.0, 'iter_decode_max_iter': 10, 'iter_decode_force_max_iter': False, 'iter_decode_with_beam': 1, 'iter_decode_with_external_reranker': False, 'retain_iter_history': False, 'retain_dropout': False, 'retain_dropout_modules': None, 'decoding_format': None, 'no_seed_provided': False, 'eos_token': None}, 'eval_lm': {'_name': None, 'output_word_probs': False, 'output_word_stats': False, 'context_window': 0, 'softmax_batch': 9223372036854775807}, 'interactive': {'_name': None, 'buffer_size': 0, 'input': '-'}, 'model': {'_name': 'wav2vec_ctc', 'w2v_path': '/media/dilip/LaCie/Nitin/vakyansh-wav2vec2-experimentation/checkpoints/pretraining/CLSRIL-23.pt', 'no_pretrained_weights': False, 'dropout_input': 0.0, 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'conv_feature_layers': '[(512, 10, 5)] + [(512, 3, 2)] 4 + [(512,2,2)] + [(512,2,2)]', 'encoder_embed_dim': 768, 'tpu': False}, 'criterion': None, 'optimizer': {'_name': 'adam', 'adam_betas': '(0.9,0.98)', 'adam_eps': 1e-06, 'weight_decay': 0.01, 'use_old_adam': False, 'tpu': False, 'lr': [0.0005]}, 'lr_scheduler': None, 'scoring': None, 'bpe': None, 'tokenizer': None, 'job_logging_cfg': {'version': 1, 'formatters': {'simple': {'format': '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'}}, 'handlers': {'console': {'class': 'logging.StreamHandler', 'formatter': 'simple', 'stream': 'ext://sys.stdout'}, 'file': {'class': 'logging.FileHandler', 'formatter': 'simple', 'filename': 'hydra_train.log'}}, 'root': {'level': 'INFO', 'handlers': ['console', 'file']}, 'disable_existing_loggers': False}} Traceback (most recent call last): File "/home/dilip/.local/lib/python3.8/site-packages/fairseq_cli/hydra_train.py", line 27, in hydra_main _hydra_main(cfg) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq_cli/hydra_train.py", line 56, in _hydra_main distributed_utils.call_main(cfg, pre_main, kwargs) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/distributed/utils.py", line 369, in call_main main(cfg, kwargs) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq_cli/train.py", line 96, in main model = task.build_model(cfg.model) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/tasks/audio_finetuning.py", line 193, in build_model model = super().build_model(model_cfg, from_checkpoint) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/tasks/audio_pretraining.py", line 197, in build_model model = super().build_model(model_cfg, from_checkpoint) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/tasks/fairseq_task.py", line 338, in build_model model = models.build_model(cfg, self, from_checkpoint) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/models/init.py", line 106, in build_model return model.build_model(cfg, task) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/models/wav2vec/wav2vec2_asr.py", line 208, in build_model w2v_encoder = Wav2VecEncoder(cfg, len(task.target_dictionary)) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/models/wav2vec/wav2vec2_asr.py", line 406, in init task = tasks.setup_task(w2v_args.task) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/tasks/init.py", line 39, in setup_task cfg = merge_with_parent(dc(), cfg) File "/home/dilip/.local/lib/python3.8/site-packages/fairseq/dataclass/utils.py", line 500, in merge_with_parent merged_cfg = OmegaConf.merge(dc, cfg) omegaconf.errors.ConfigKeyError: Key 'eval_wer' not in 'AudioPretrainingConfig' full_key: eval_wer reference_type=Optional[AudioPretrainingConfig] object_type=AudioPretrainingConfig
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.