07/20/2023 11:04:54 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True 07/20/2023 11:04:54 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, auto_find_batch_size=False, bf16=False, bf16_full_eval=False, data_seed=None, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_pin_memory=True, ddp_bucket_cap_mb=None, ddp_find_unused_parameters=None, ddp_timeout=1800, debug=[], deepspeed=None, disable_tqdm=False, do_eval=True, do_predict=False, do_train=True, eval_accumulation_steps=None, eval_delay=0, eval_steps=1000, evaluation_strategy=steps, fp16=True, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, fsdp=[], fsdp_min_num_params=0, fsdp_transformer_layer_cls_to_wrap=None, full_determinism=False, generation_max_length=225, generation_num_beams=None, gradient_accumulation_steps=1, gradient_checkpointing=True, greater_is_better=False, group_by_length=False, half_precision_backend=auto, hub_model_id=None, hub_private_repo=False, hub_strategy=every_save, hub_token=, ignore_data_skip=False, include_inputs_for_metrics=False, jit_mode_eval=False, label_names=None, label_smoothing_factor=0.0, learning_rate=1e-05, length_column_name=input_length, load_best_model_at_end=True, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Jul20_11-04-54_tknadmin-System-Product-Name, logging_first_step=False, logging_nan_inf_filter=True, logging_steps=25, logging_strategy=steps, lr_scheduler_type=linear, max_grad_norm=1.0, max_steps=5000, metric_for_best_model=wer, mp_parameters=, no_cuda=False, num_train_epochs=3.0, optim=adamw_hf, optim_args=None, output_dir=./, overwrite_output_dir=True, past_index=-1, per_device_eval_batch_size=16, per_device_train_batch_size=32, predict_with_generate=True, prediction_loss_only=False, push_to_hub=True, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=, ray_scope=last, remove_unused_columns=True, report_to=['tensorboard'], resume_from_checkpoint=None, run_name=./, save_on_each_node=False, save_steps=1000, save_strategy=steps, save_total_limit=None, seed=42, sharded_ddp=[], skip_memory_metrics=True, sortish_sampler=False, tf32=None, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, torchdynamo=None, tpu_metrics_debug=False, tpu_num_cores=None, use_ipex=False, use_legacy_prediction_loop=False, use_mps_device=False, warmup_ratio=0.0, warmup_steps=500, weight_decay=0.0, xpu_backend=None, ) 07/20/2023 11:04:54 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, auto_find_batch_size=False, bf16=False, bf16_full_eval=False, data_seed=None, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_pin_memory=True, ddp_bucket_cap_mb=None, ddp_find_unused_parameters=None, ddp_timeout=1800, debug=[], deepspeed=None, disable_tqdm=False, do_eval=True, do_predict=False, do_train=True, eval_accumulation_steps=None, eval_delay=0, eval_steps=1000, evaluation_strategy=steps, fp16=True, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, fsdp=[], fsdp_min_num_params=0, fsdp_transformer_layer_cls_to_wrap=None, full_determinism=False, generation_max_length=225, generation_num_beams=None, gradient_accumulation_steps=1, gradient_checkpointing=True, greater_is_better=False, group_by_length=False, half_precision_backend=auto, hub_model_id=None, hub_private_repo=False, hub_strategy=every_save, hub_token=, ignore_data_skip=False, include_inputs_for_metrics=False, jit_mode_eval=False, label_names=None, label_smoothing_factor=0.0, learning_rate=1e-05, length_column_name=input_length, load_best_model_at_end=True, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Jul20_11-04-54_tknadmin-System-Product-Name, logging_first_step=False, logging_nan_inf_filter=True, logging_steps=25, logging_strategy=steps, lr_scheduler_type=linear, max_grad_norm=1.0, max_steps=5000, metric_for_best_model=wer, mp_parameters=, no_cuda=False, num_train_epochs=3.0, optim=adamw_hf, optim_args=None, output_dir=./, overwrite_output_dir=True, past_index=-1, per_device_eval_batch_size=16, per_device_train_batch_size=32, predict_with_generate=True, prediction_loss_only=False, push_to_hub=True, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=, ray_scope=last, remove_unused_columns=True, report_to=['tensorboard'], resume_from_checkpoint=None, run_name=./, save_on_each_node=False, save_steps=1000, save_strategy=steps, save_total_limit=None, seed=42, sharded_ddp=[], skip_memory_metrics=True, sortish_sampler=False, tf32=None, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, torchdynamo=None, tpu_metrics_debug=False, tpu_num_cores=None, use_ipex=False, use_legacy_prediction_loop=False, use_mps_device=False, warmup_ratio=0.0, warmup_steps=500, weight_decay=0.0, xpu_backend=None, ) 07/20/2023 11:04:56 - INFO - datasets.utils.file_utils - https://huggingface.co/datasets/mozilla-foundation/common_voice_13_0/resolve/main/common_voice_13_0.py not found in cache or force_download set to True, downloading to /home/xezpeleta/.cache/huggingface/datasets/downloads/tmp33netx5y Downloading builder script: 0%| | 0.00/8.18k [00:00 main() File "/home/xezpeleta/dev/whisper-small-eu-v2/run_speech_recognition_seq2seq_streaming.py", line 365, in main raw_datasets["eval"] = load_maybe_streaming_dataset( File "/home/xezpeleta/dev/whisper-small-eu-v2/run_speech_recognition_seq2seq_streaming.py", line 285, in load_maybe_streaming_dataset dataset = load_dataset(dataset_name, dataset_config_name, split=split, streaming=streaming, **kwargs) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/load.py", line 1734, in load_dataset builder_instance = load_dataset_builder( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/load.py", line 1492, in load_dataset_builder dataset_module = dataset_module_factory( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/load.py", line 1187, in dataset_module_factory return HubDatasetModuleFactoryWithScript( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/load.py", line 863, in __init__ increase_load_count(name, resource_type="dataset") File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/load.py", line 160, in increase_load_count head_hf_s3(name, filename=name + ".py", dataset=(resource_type == "dataset")) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 96, in head_hf_s3 return http_head( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 390, in http_head response = _request_with_retry( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/datasets/utils/file_utils.py", line 319, in _request_with_retry response = requests.request(method=method.upper(), url=url, timeout=timeout, **params) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/requests/api.py", line 59, in request return session.request(method=method, url=url, **kwargs) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/requests/sessions.py", line 587, in request resp = self.send(prep, **send_kwargs) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/requests/sessions.py", line 701, in send r = adapter.send(request, **kwargs) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/requests/adapters.py", line 489, in send resp = conn.urlopen( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/connectionpool.py", line 703, in urlopen httplib_response = self._make_request( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/connectionpool.py", line 386, in _make_request self._validate_conn(conn) File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/connectionpool.py", line 1042, in _validate_conn conn.connect() File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/connection.py", line 414, in connect self.sock = ssl_wrap_socket( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/util/ssl_.py", line 449, in ssl_wrap_socket ssl_sock = _ssl_wrap_socket_impl( File "/home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/urllib3/util/ssl_.py", line 493, in _ssl_wrap_socket_impl return ssl_context.wrap_socket(sock, server_hostname=server_hostname) File "/usr/lib/python3.10/ssl.py", line 513, in wrap_socket return self.sslsocket_class._create( File "/usr/lib/python3.10/ssl.py", line 1071, in _create self.do_handshake() File "/usr/lib/python3.10/ssl.py", line 1342, in do_handshake self._sslobj.do_handshake() KeyboardInterrupt 07/20/2023 11:05:06 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True 07/20/2023 11:05:06 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, auto_find_batch_size=False, bf16=False, bf16_full_eval=False, data_seed=None, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_pin_memory=True, ddp_bucket_cap_mb=None, ddp_find_unused_parameters=None, ddp_timeout=1800, debug=[], deepspeed=None, disable_tqdm=False, do_eval=True, do_predict=False, do_train=True, eval_accumulation_steps=None, eval_delay=0, eval_steps=1000, evaluation_strategy=steps, fp16=True, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, fsdp=[], fsdp_min_num_params=0, fsdp_transformer_layer_cls_to_wrap=None, full_determinism=False, generation_max_length=225, generation_num_beams=None, gradient_accumulation_steps=1, gradient_checkpointing=True, greater_is_better=False, group_by_length=False, half_precision_backend=auto, hub_model_id=None, hub_private_repo=False, hub_strategy=every_save, hub_token=, ignore_data_skip=False, include_inputs_for_metrics=False, jit_mode_eval=False, label_names=None, label_smoothing_factor=0.0, learning_rate=1e-05, length_column_name=input_length, load_best_model_at_end=True, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Jul20_11-05-05_tknadmin-System-Product-Name, logging_first_step=False, logging_nan_inf_filter=True, logging_steps=25, logging_strategy=steps, lr_scheduler_type=linear, max_grad_norm=1.0, max_steps=5000, metric_for_best_model=wer, mp_parameters=, no_cuda=False, num_train_epochs=3.0, optim=adamw_hf, optim_args=None, output_dir=./, overwrite_output_dir=True, past_index=-1, per_device_eval_batch_size=16, per_device_train_batch_size=32, predict_with_generate=True, prediction_loss_only=False, push_to_hub=True, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=, ray_scope=last, remove_unused_columns=True, report_to=['tensorboard'], resume_from_checkpoint=None, run_name=./, save_on_each_node=False, save_steps=1000, save_strategy=steps, save_total_limit=None, seed=42, sharded_ddp=[], skip_memory_metrics=True, sortish_sampler=False, tf32=None, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, torchdynamo=None, tpu_metrics_debug=False, tpu_num_cores=None, use_ipex=False, use_legacy_prediction_loop=False, use_mps_device=False, warmup_ratio=0.0, warmup_steps=500, weight_decay=0.0, xpu_backend=None, ) 07/20/2023 11:05:06 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments( _n_gpu=1, adafactor=False, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, auto_find_batch_size=False, bf16=False, bf16_full_eval=False, data_seed=None, dataloader_drop_last=False, dataloader_num_workers=0, dataloader_pin_memory=True, ddp_bucket_cap_mb=None, ddp_find_unused_parameters=None, ddp_timeout=1800, debug=[], deepspeed=None, disable_tqdm=False, do_eval=True, do_predict=False, do_train=True, eval_accumulation_steps=None, eval_delay=0, eval_steps=1000, evaluation_strategy=steps, fp16=True, fp16_backend=auto, fp16_full_eval=False, fp16_opt_level=O1, fsdp=[], fsdp_min_num_params=0, fsdp_transformer_layer_cls_to_wrap=None, full_determinism=False, generation_max_length=225, generation_num_beams=None, gradient_accumulation_steps=1, gradient_checkpointing=True, greater_is_better=False, group_by_length=False, half_precision_backend=auto, hub_model_id=None, hub_private_repo=False, hub_strategy=every_save, hub_token=, ignore_data_skip=False, include_inputs_for_metrics=False, jit_mode_eval=False, label_names=None, label_smoothing_factor=0.0, learning_rate=1e-05, length_column_name=input_length, load_best_model_at_end=True, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Jul20_11-05-05_tknadmin-System-Product-Name, logging_first_step=False, logging_nan_inf_filter=True, logging_steps=25, logging_strategy=steps, lr_scheduler_type=linear, max_grad_norm=1.0, max_steps=5000, metric_for_best_model=wer, mp_parameters=, no_cuda=False, num_train_epochs=3.0, optim=adamw_hf, optim_args=None, output_dir=./, overwrite_output_dir=True, past_index=-1, per_device_eval_batch_size=16, per_device_train_batch_size=32, predict_with_generate=True, prediction_loss_only=False, push_to_hub=True, push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=, ray_scope=last, remove_unused_columns=True, report_to=['tensorboard'], resume_from_checkpoint=None, run_name=./, save_on_each_node=False, save_steps=1000, save_strategy=steps, save_total_limit=None, seed=42, sharded_ddp=[], skip_memory_metrics=True, sortish_sampler=False, tf32=None, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, torchdynamo=None, tpu_metrics_debug=False, tpu_num_cores=None, use_ipex=False, use_legacy_prediction_loop=False, use_mps_device=False, warmup_ratio=0.0, warmup_steps=500, weight_decay=0.0, xpu_backend=None, ) 07/20/2023 11:05:08 - INFO - datasets.info - Loading Dataset Infos from /home/xezpeleta/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_13_0/2506e9a8950f5807ceae08c2920e814222909fd7f477b74f5d225802e9f04055 07/20/2023 11:05:10 - INFO - datasets.info - Loading Dataset Infos from /home/xezpeleta/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_13_0/2506e9a8950f5807ceae08c2920e814222909fd7f477b74f5d225802e9f04055 07/20/2023 11:05:13 - INFO - datasets.info - Loading Dataset Infos from /home/xezpeleta/.cache/huggingface/modules/datasets_modules/datasets/mozilla-foundation--common_voice_13_0/2506e9a8950f5807ceae08c2920e814222909fd7f477b74f5d225802e9f04055 Downloading: 0%| | 0.00/1.97k [00:00> loading configuration file config.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/config.json [INFO|configuration_utils.py:706] 2023-07-20 11:05:14,156 >> Model config WhisperConfig { "_name_or_path": "openai/whisper-small", "activation_dropout": 0.0, "activation_function": "gelu", "architectures": [ "WhisperForConditionalGeneration" ], "attention_dropout": 0.0, "begin_suppress_tokens": [ 220, 50257 ], "bos_token_id": 50257, "d_model": 768, "decoder_attention_heads": 12, "decoder_ffn_dim": 3072, "decoder_layerdrop": 0.0, "decoder_layers": 12, "decoder_start_token_id": 50258, "dropout": 0.0, "encoder_attention_heads": 12, "encoder_ffn_dim": 3072, "encoder_layerdrop": 0.0, "encoder_layers": 12, "eos_token_id": 50257, "forced_decoder_ids": [ [ 1, 50259 ], [ 2, 50359 ], [ 3, 50363 ] ], "init_std": 0.02, "is_encoder_decoder": true, "max_length": 448, "max_source_positions": 1500, "max_target_positions": 448, "model_type": "whisper", "num_hidden_layers": 12, "num_mel_bins": 80, "pad_token_id": 50257, "scale_embedding": false, "suppress_tokens": [ 1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93, 359, 503, 522, 542, 873, 893, 902, 918, 922, 931, 1350, 1853, 1982, 2460, 2627, 3246, 3253, 3268, 3536, 3846, 3961, 4183, 4667, 6585, 6647, 7273, 9061, 9383, 10428, 10929, 11938, 12033, 12331, 12562, 13793, 14157, 14635, 15265, 15618, 16553, 16604, 18362, 18956, 20075, 21675, 22520, 26130, 26161, 26435, 28279, 29464, 31650, 32302, 32470, 36865, 42863, 47425, 49870, 50254, 50258, 50360, 50361, 50362 ], "torch_dtype": "float32", "transformers_version": "4.26.0.dev0", "use_cache": true, "vocab_size": 51865 } [INFO|feature_extraction_utils.py:464] 2023-07-20 11:05:14,454 >> loading configuration file preprocessor_config.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/preprocessor_config.json [INFO|feature_extraction_utils.py:501] 2023-07-20 11:05:14,466 >> Feature extractor WhisperFeatureExtractor { "chunk_length": 30, "feature_extractor_type": "WhisperFeatureExtractor", "feature_size": 80, "hop_length": 160, "mel_filters": [ [ -0.0, 0.02486259490251541, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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0.003141313325613737, 0.002692554146051407, 0.0022437951993197203, 0.00179503601975739, 0.0013462770730257034, 0.000897518009878695, 0.0004487590049393475, 0.0 ] ], "n_fft": 400, "n_samples": 480000, "nb_max_frames": 3000, "padding_side": "right", "padding_value": 0.0, "processor_class": "WhisperProcessor", "return_attention_mask": false, "sampling_rate": 16000 } Downloading: 0%| | 0.00/842 [00:00> loading file vocab.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/vocab.json [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,953 >> loading file tokenizer.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/tokenizer.json [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,954 >> loading file merges.txt from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/merges.txt [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,954 >> loading file normalizer.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/normalizer.json [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,954 >> loading file added_tokens.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/added_tokens.json [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,954 >> loading file special_tokens_map.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/special_tokens_map.json [INFO|tokenization_utils_base.py:1799] 2023-07-20 11:05:17,954 >> loading file tokenizer_config.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/tokenizer_config.json [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|startoftranscript|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|en|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|zh|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|de|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|es|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ru|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ko|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|fr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ja|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|pt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|tr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|pl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ca|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|nl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ar|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|sv|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|it|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|id|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|hi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|fi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|vi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|he|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|uk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|el|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ms|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|cs|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ro|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|da|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|hu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ta|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|no|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|th|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ur|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|hr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|bg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|lt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|la|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|mi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|ml|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|cy|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|sk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|te|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|fa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|lv|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,005 >> Adding <|bn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|az|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|kn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|et|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|mk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|br|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|eu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|is|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|hy|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ne|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|mn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|bs|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|kk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sq|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|gl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|mr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|pa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|si|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|km|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|yo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|so|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|af|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|oc|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ka|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|be|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|tg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sd|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|gu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|am|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|yi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|lo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|uz|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|fo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ht|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ps|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|tk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|nn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|mt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|sa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|lb|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|my|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|bo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|tl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|mg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|as|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|tt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|haw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ln|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ha|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|ba|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|jw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|su|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|translate|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|transcribe|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|startoflm|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|startofprev|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|nocaptions|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:18,006 >> Adding <|notimestamps|> to the vocabulary [INFO|modeling_utils.py:2264] 2023-07-20 11:05:18,193 >> loading weights file pytorch_model.bin from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/pytorch_model.bin [INFO|configuration_utils.py:523] 2023-07-20 11:05:19,349 >> Generate config GenerationConfig { "begin_suppress_tokens": [ 220, 50257 ], "bos_token_id": 50257, "decoder_start_token_id": 50258, "eos_token_id": 50257, "max_length": 448, "pad_token_id": 50257, "transformers_version": "4.26.0.dev0", "use_cache": false } [INFO|modeling_utils.py:2842] 2023-07-20 11:05:20,532 >> All model checkpoint weights were used when initializing WhisperForConditionalGeneration. [INFO|modeling_utils.py:2850] 2023-07-20 11:05:20,532 >> All the weights of WhisperForConditionalGeneration were initialized from the model checkpoint at openai/whisper-small. If your task is similar to the task the model of the checkpoint was trained on, you can already use WhisperForConditionalGeneration for predictions without further training. Downloading: 0%| | 0.00/3.51k [00:00> loading configuration file generation_config.json from cache at /home/xezpeleta/.cache/huggingface/hub/models--openai--whisper-small/snapshots/dc81969cac97c87ddad61ccc5012b389c81e8dd4/generation_config.json [INFO|configuration_utils.py:523] 2023-07-20 11:05:21,329 >> Generate config GenerationConfig { "begin_suppress_tokens": [ 220, 50257 ], "bos_token_id": 50257, "decoder_start_token_id": 50258, "eos_token_id": 50257, "forced_decoder_ids": [ [ 1, null ], [ 2, 50359 ] ], "max_length": 448, "pad_token_id": 50257, "suppress_tokens": [ 1, 2, 7, 8, 9, 10, 14, 25, 26, 27, 28, 29, 31, 58, 59, 60, 61, 62, 63, 90, 91, 92, 93, 359, 503, 522, 542, 873, 893, 902, 918, 922, 931, 1350, 1853, 1982, 2460, 2627, 3246, 3253, 3268, 3536, 3846, 3961, 4183, 4667, 6585, 6647, 7273, 9061, 9383, 10428, 10929, 11938, 12033, 12331, 12562, 13793, 14157, 14635, 15265, 15618, 16553, 16604, 18362, 18956, 20075, 21675, 22520, 26130, 26161, 26435, 28279, 29464, 31650, 32302, 32470, 36865, 42863, 47425, 49870, 50254, 50258, 50358, 50359, 50360, 50361, 50362 ], "transformers_version": "4.26.0.dev0" } [INFO|feature_extraction_utils.py:368] 2023-07-20 11:05:22,382 >> Feature extractor saved in ./preprocessor_config.json [INFO|tokenization_utils_base.py:2157] 2023-07-20 11:05:22,382 >> tokenizer config file saved in ./tokenizer_config.json [INFO|tokenization_utils_base.py:2164] 2023-07-20 11:05:22,382 >> Special tokens file saved in ./special_tokens_map.json [INFO|tokenization_utils_base.py:2210] 2023-07-20 11:05:22,382 >> added tokens file saved in ./added_tokens.json [INFO|configuration_utils.py:447] 2023-07-20 11:05:22,423 >> Configuration saved in ./config.json [INFO|image_processing_utils.py:294] 2023-07-20 11:05:22,424 >> loading configuration file ./preprocessor_config.json [INFO|feature_extraction_utils.py:462] 2023-07-20 11:05:22,428 >> loading configuration file ./preprocessor_config.json [INFO|feature_extraction_utils.py:501] 2023-07-20 11:05:22,434 >> Feature extractor WhisperFeatureExtractor { "chunk_length": 30, "feature_extractor_type": "WhisperFeatureExtractor", "feature_size": 80, "hop_length": 160, "mel_filters": [ [ -0.0, 0.02486259490251541, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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"WhisperProcessor", "return_attention_mask": false, "sampling_rate": 16000 } [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file vocab.json [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file tokenizer.json [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file merges.txt [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file normalizer.json [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file added_tokens.json [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file special_tokens_map.json [INFO|tokenization_utils_base.py:1797] 2023-07-20 11:05:22,434 >> loading file tokenizer_config.json [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,463 >> Adding <|startoftranscript|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,463 >> Adding <|en|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,463 >> Adding <|zh|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|de|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|es|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ru|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ko|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|fr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ja|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|pt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|tr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|pl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ca|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|nl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ar|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sv|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|it|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|id|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|hi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|fi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|vi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|he|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|uk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|el|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ms|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|cs|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ro|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|da|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|hu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ta|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|no|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|th|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ur|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|hr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|bg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|lt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|la|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|mi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ml|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|cy|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|te|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|fa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|lv|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|bn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|az|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|kn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|et|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|mk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|br|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|eu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|is|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|hy|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|ne|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|mn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|bs|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|kk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sq|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|sw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|gl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,464 >> Adding <|mr|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|pa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|si|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|km|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|sn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|yo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|so|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|af|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|oc|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ka|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|be|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|tg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|sd|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|gu|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|am|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|yi|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|lo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|uz|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|fo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ht|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ps|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|tk|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|nn|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|mt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|sa|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|lb|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|my|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|bo|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|tl|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|mg|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|as|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|tt|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|haw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ln|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ha|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|ba|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|jw|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|su|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|translate|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|transcribe|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|startoflm|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|startofprev|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|nocaptions|> to the vocabulary [INFO|tokenization_utils.py:426] 2023-07-20 11:05:22,465 >> Adding <|notimestamps|> to the vocabulary /home/xezpeleta/dev/whisper-small-eu-v2/./ is already a clone of https://huggingface.co/xezpeleta/whisper-small-eu-v2. Make sure you pull the latest changes with `repo.git_pull()`. 07/20/2023 11:05:24 - WARNING - huggingface_hub.repository - /home/xezpeleta/dev/whisper-small-eu-v2/./ is already a clone of https://huggingface.co/xezpeleta/whisper-small-eu-v2. Make sure you pull the latest changes with `repo.git_pull()`. [INFO|trainer.py:511] 2023-07-20 11:05:26,572 >> max_steps is given, it will override any value given in num_train_epochs [INFO|trainer.py:565] 2023-07-20 11:05:26,572 >> Using cuda_amp half precision backend /home/xezpeleta/dev/hf_env/lib/python3.10/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning warnings.warn( [INFO|trainer.py:1641] 2023-07-20 11:05:26,581 >> ***** Running training ***** [INFO|trainer.py:1642] 2023-07-20 11:05:26,581 >> Num examples = 160000 [INFO|trainer.py:1643] 2023-07-20 11:05:26,581 >> Num Epochs = 9223372036854775807 [INFO|trainer.py:1644] 2023-07-20 11:05:26,581 >> Instantaneous batch size per device = 32 [INFO|trainer.py:1645] 2023-07-20 11:05:26,581 >> Total train batch size (w. parallel, distributed & accumulation) = 32 [INFO|trainer.py:1646] 2023-07-20 11:05:26,581 >> Gradient Accumulation steps = 1 [INFO|trainer.py:1647] 2023-07-20 11:05:26,581 >> Total optimization steps = 5000 [INFO|trainer.py:1648] 2023-07-20 11:05:26,582 >> Number of trainable parameters = 241734912 0%| | 0/5000 [00:00> The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 0%| | 1/5000 [01:01<84:57:02, 61.18s/it] 0%| | 2/5000 [01:05<38:28:27, 27.71s/it] 0%| | 3/5000 [01:10<24:02:12, 17.32s/it] 0%| | 4/5000 [01:14<16:37:41, 11.98s/it] 0%| | 5/5000 [01:17<12:25:37, 8.96s/it] 0%| | 6/5000 [01:23<10:42:07, 7.71s/it] 0%| | 7/5000 [01:26<8:52:23, 6.40s/it] 0%| | 8/5000 [01:32<8:21:02, 6.02s/it] 0%| | 9/5000 [01:35<7:20:27, 5.30s/it] 0%| | 10/5000 [01:39<6:38:28, 4.79s/it] 0%| | 11/5000 [01:43<6:09:36, 4.45s/it] 0%| | 12/5000 [01:46<5:50:02, 4.21s/it] 0%| | 13/5000 [01:52<6:33:27, 4.73s/it] 0%| | 14/5000 [01:57<6:32:33, 4.72s/it] 0%| | 15/5000 [02:02<6:46:12, 4.89s/it] 0%| | 16/5000 [02:06<6:21:44, 4.60s/it] 0%| | 17/5000 [02:10<5:57:44, 4.31s/it] 0%| | 18/5000 [02:14<6:02:55, 4.37s/it] 0%| | 19/5000 [02:19<6:16:06, 4.53s/it] 0%| | 20/5000 [02:24<6:27:20, 4.67s/it] 0%| | 21/5000 [02:29<6:30:25, 4.70s/it] 0%| | 22/5000 [02:35<7:03:53, 5.11s/it] 0%| 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4.4e-07, 'epoch': 0.01} {'loss': 1.4728, 'learning_rate': 9.400000000000001e-07, 'epoch': 0.01} {'loss': 1.1563, 'learning_rate': 1.44e-06, 'epoch': 0.01} {'loss': 0.9368, 'learning_rate': 1.94e-06, 'epoch': 0.02} {'loss': 0.8889, 'learning_rate': 2.4400000000000004e-06, 'epoch': 0.03} {'loss': 0.8114, 'learning_rate': 2.9400000000000002e-06, 'epoch': 0.03} {'loss': 0.6924, 'learning_rate': 3.44e-06, 'epoch': 0.04} {'loss': 0.661, 'learning_rate': 3.94e-06, 'epoch': 0.04} {'loss': 0.6427, 'learning_rate': 4.440000000000001e-06, 'epoch': 0.04} {'loss': 0.5217, 'learning_rate': 4.94e-06, 'epoch': 0.05} {'loss': 0.4991, 'learning_rate': 5.4400000000000004e-06, 'epoch': 0.06} {'loss': 0.4768, 'learning_rate': 5.94e-06, 'epoch': 0.06} {'loss': 0.4632, 'learning_rate': 6.440000000000001e-06, 'epoch': 0.07} {'loss': 0.4289, 'learning_rate': 6.9400000000000005e-06, 'epoch': 0.07} {'loss': 0.404, 'learning_rate': 7.440000000000001e-06, 'epoch': 0.07} {'loss': 0.3833, 'learning_rate': 7.94e-06, 'epoch': 0.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.06it/s] Reading metadata...: 10918it [00:00, 20906.26it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 3.24it/s] Reading metadata...: 6591it [00:00, 20005.30it/s] 8%|▊ | 413/5000 [32:09<18:15:35, 14.33s/it] 8%|▊ | 414/5000 [32:13<14:15:46, 11.20s/it] 8%|▊ | 415/5000 [32:18<11:42:05, 9.19s/it] 8%|▊ | 416/5000 [32:22<9:41:13, 7.61s/it] 8%|▊ | 417/5000 [32:26<8:35:16, 6.75s/it] 8%|▊ | 418/5000 [32:31<7:48:17, 6.13s/it] 8%|▊ | 419/5000 [32:35<6:56:42, 5.46s/it] 8%|▊ | 420/5000 [32:39<6:34:38, 5.17s/it] 8%|▊ | 421/5000 [32:43<6:06:45, 4.81s/it] 8%|▊ | 422/5000 [32:48<5:59:32, 4.71s/it] 8%|▊ | 423/5000 [32:53<5:59:16, 4.71s/it] 8%|▊ | 424/5000 [32:56<5:40:54, 4.47s/it] 8%|▊ | 425/5000 [33:02<6:08:56, 4.84s/it] 8%|▊ | 425/5000 [33:02<6:08:56, 4.84s/it] 9%|▊ | 426/5000 [33:06<5:53:16, 4.63s/it] 9%|▊ | 427/5000 [33:12<6:16:37, 4.94s/it] 9%|▊ | 428/5000 [33:17<6:09:50, 4.85s/it] 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[1:02:21<2:23:40, 2.06s/it] 16%|█▋ | 824/5000 [1:02:23<2:20:49, 2.02s/it]{'loss': 0.4201, 'learning_rate': 8.44e-06, 'epoch': 1.0} {'loss': 0.3989, 'learning_rate': 8.94e-06, 'epoch': 1.01} {'loss': 0.3453, 'learning_rate': 9.440000000000001e-06, 'epoch': 1.01} {'loss': 0.3559, 'learning_rate': 9.940000000000001e-06, 'epoch': 1.02} {'loss': 0.3429, 'learning_rate': 9.951111111111111e-06, 'epoch': 1.02} {'loss': 0.3701, 'learning_rate': 9.895555555555557e-06, 'epoch': 1.03} {'loss': 0.3084, 'learning_rate': 9.84e-06, 'epoch': 1.03} {'loss': 0.2956, 'learning_rate': 9.784444444444445e-06, 'epoch': 1.04} {'loss': 0.2923, 'learning_rate': 9.72888888888889e-06, 'epoch': 1.04} {'loss': 0.2786, 'learning_rate': 9.673333333333334e-06, 'epoch': 1.05} {'loss': 0.2427, 'learning_rate': 9.617777777777778e-06, 'epoch': 1.05} {'loss': 0.2387, 'learning_rate': 9.562222222222223e-06, 'epoch': 1.06} {'loss': 0.2371, 'learning_rate': 9.506666666666667e-06, 'epoch': 1.06} {'loss': 0.2114, 'learning_rate': 9.451111111111112e-06, 'epoch': 1.07} {'loss': 0.1894, 'learning_rate': 9.395555555555556e-06, 'epoch': 1.07} {'loss': 0.1867, 'learning_rate': 9.340000000000002e-06, 'epoch': 1.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.07it/s] Reading metadata...: 10918it [00:00, 21045.66it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 3.26it/s] Reading metadata...: 6591it [00:00, 20102.47it/s] 16%|█▋ | 825/5000 [1:03:13<18:49:42, 16.24s/it] 16%|█▋ | 825/5000 [1:03:13<18:49:42, 16.24s/it] 17%|█▋ | 826/5000 [1:03:17<14:45:01, 12.72s/it] 17%|█▋ | 827/5000 [1:03:21<11:40:32, 10.07s/it] 17%|█▋ | 828/5000 [1:03:25<9:33:23, 8.25s/it] 17%|█▋ | 829/5000 [1:03:29<8:02:10, 6.94s/it] 17%|█▋ | 830/5000 [1:03:34<7:18:52, 6.31s/it] 17%|█▋ | 831/5000 [1:03:38<6:41:38, 5.78s/it] 17%|█▋ | 832/5000 [1:03:43<6:19:39, 5.47s/it] 17%|█▋ | 833/5000 [1:03:48<6:13:53, 5.38s/it] 17%|█▋ | 834/5000 [1:03:53<5:48:48, 5.02s/it] 17%|█▋ | 835/5000 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12:21:36,214 >> ***** Running Evaluation ***** [INFO|trainer.py:2959] 2023-07-20 12:21:36,214 >> Num examples: Unknown [INFO|trainer.py:2960] 2023-07-20 12:21:36,214 >> Batch size = 16 {'loss': 0.1927, 'learning_rate': 9.284444444444444e-06, 'epoch': 2.0} {'loss': 0.1951, 'learning_rate': 9.22888888888889e-06, 'epoch': 2.01} {'loss': 0.1775, 'learning_rate': 9.173333333333334e-06, 'epoch': 2.01} {'loss': 0.1672, 'learning_rate': 9.117777777777778e-06, 'epoch': 2.02} {'loss': 0.1591, 'learning_rate': 9.062222222222224e-06, 'epoch': 2.02} {'loss': 0.1703, 'learning_rate': 9.006666666666666e-06, 'epoch': 2.03} {'loss': 0.1636, 'learning_rate': 8.951111111111112e-06, 'epoch': 2.03} {'loss': 0.1413, 'learning_rate': 8.895555555555556e-06, 'epoch': 2.04} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 1.41it/s] Reading metadata...: 6591it [00:00, 9037.42it/s] [INFO|trainer_utils.py:689] 2023-07-20 12:21:39,930 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 20%|██ | 1000/5000 [1:32:13<4:45:27, 4.28s/it][INFO|trainer.py:2700] 2023-07-20 12:37:39,717 >> Saving model checkpoint to ./checkpoint-1000 [INFO|configuration_utils.py:447] 2023-07-20 12:37:39,718 >> Configuration saved in ./checkpoint-1000/config.json [INFO|modeling_utils.py:1693] 2023-07-20 12:37:40,970 >> Model weights saved in ./checkpoint-1000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 12:37:40,982 >> Feature extractor saved in ./checkpoint-1000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2023-07-20 12:37:44,323 >> Feature extractor saved in ./preprocessor_config.json 20%|██ | 1001/5000 [1:32:54<338:21:54, 304.60s/it] 20%|██ | 1002/5000 [1:32:59<238:14:15, 214.52s/it] 20%|██ | 1003/5000 [1:33:03<168:14:47, 151.54s/it] 20%|██ | 1004/5000 [1:33:07<119:00:01, 107.21s/it] 20%|██ | 1005/5000 [1:33:11<84:32:55, 76.19s/it] 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8.617777777777778e-06, 'epoch': 2.06} {'loss': 0.1054, 'learning_rate': 8.562222222222224e-06, 'epoch': 2.07} {'loss': 0.0912, 'learning_rate': 8.506666666666668e-06, 'epoch': 2.07} {'loss': 0.0915, 'learning_rate': 8.451111111111112e-06, 'epoch': 2.08} {'loss': 0.0901, 'learning_rate': 8.395555555555557e-06, 'epoch': 2.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.04it/s] Reading metadata...: 10918it [00:00, 20601.77it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.86it/s] Reading metadata...: 6591it [00:00, 17139.30it/s] 25%|██▍ | 1237/5000 [1:50:23<14:37:40, 13.99s/it] 25%|██▍ | 1238/5000 [1:50:26<11:26:50, 10.95s/it] 25%|██▍ | 1239/5000 [1:50:30<9:12:19, 8.81s/it] 25%|██▍ | 1240/5000 [1:50:35<7:51:03, 7.52s/it] 25%|██▍ | 1241/5000 [1:50:39<6:43:15, 6.44s/it] 25%|██▍ | 1242/5000 [1:50:43<6:08:42, 5.89s/it] 25%|██▍ | 1243/5000 [1:50:47<5:31:40, 5.30s/it] 25%|██▍ | 1244/5000 [1:50:52<5:15:52, 5.05s/it] 25%|██▍ | 1245/5000 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'learning_rate': 7.451111111111111e-06, 'epoch': 4.0} {'loss': 0.0447, 'learning_rate': 7.395555555555556e-06, 'epoch': 4.01} {'loss': 0.0362, 'learning_rate': 7.340000000000001e-06, 'epoch': 4.01} {'loss': 0.0368, 'learning_rate': 7.284444444444445e-06, 'epoch': 4.02} {'loss': 0.0367, 'learning_rate': 7.22888888888889e-06, 'epoch': 4.02} {'loss': 0.0391, 'learning_rate': 7.173333333333335e-06, 'epoch': 4.03} {'loss': 0.0331, 'learning_rate': 7.117777777777778e-06, 'epoch': 4.03} {'loss': 0.028, 'learning_rate': 7.062222222222223e-06, 'epoch': 4.04} {'loss': 0.0315, 'learning_rate': 7.006666666666667e-06, 'epoch': 4.04} {'loss': 0.0308, 'learning_rate': 6.951111111111112e-06, 'epoch': 4.05} {'loss': 0.0248, 'learning_rate': 6.8955555555555565e-06, 'epoch': 4.05} {'loss': 0.023, 'learning_rate': 6.8400000000000014e-06, 'epoch': 4.06} {'loss': 0.0233, 'learning_rate': 6.784444444444445e-06, 'epoch': 4.06} {'loss': 0.0236, 'learning_rate': 6.7288888888888895e-06, 'epoch': 4.07} {'loss': 0.0181, 'learning_rate': 6.6733333333333335e-06, 'epoch': 4.07} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:01, 1.06s/it] Reading metadata...: 6591it [00:01, 6038.24it/s] [INFO|trainer_utils.py:689] 2023-07-20 13:53:48,489 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 40%|████ | 2000/5000 [3:04:10<3:24:32, 4.09s/it][INFO|trainer.py:2700] 2023-07-20 14:09:37,141 >> Saving model checkpoint to ./checkpoint-2000 [INFO|configuration_utils.py:447] 2023-07-20 14:09:37,142 >> Configuration saved in ./checkpoint-2000/config.json [INFO|modeling_utils.py:1693] 2023-07-20 14:09:38,420 >> Model weights saved in ./checkpoint-2000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 14:09:38,430 >> Feature extractor saved in ./checkpoint-2000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2023-07-20 14:09:43,863 >> Feature extractor saved in ./preprocessor_config.json Several commits (2) will be pushed upstream. {'eval_loss': 0.33755382895469666, 'eval_wer': 20.286362347604197, 'eval_runtime': 952.5181, 'eval_samples_per_second': 6.92, 'eval_steps_per_second': 0.433, 'epoch': 4.07} 07/20/2023 14:10:12 - WARNING - 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'learning_rate': 5.062222222222222e-06, 'epoch': 6.05} {'loss': 0.0057, 'learning_rate': 5.006666666666667e-06, 'epoch': 6.06} {'loss': 0.0064, 'learning_rate': 4.951111111111111e-06, 'epoch': 6.06} {'loss': 0.0053, 'learning_rate': 4.895555555555556e-06, 'epoch': 6.07} {'loss': 0.0047, 'learning_rate': 4.84e-06, 'epoch': 6.07} {'loss': 0.005, 'learning_rate': 4.784444444444445e-06, 'epoch': 6.08} {'loss': 0.0047, 'learning_rate': 4.728888888888889e-06, 'epoch': 6.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 1.88it/s] Reading metadata...: 10918it [00:00, 19177.43it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.90it/s] Reading metadata...: 6591it [00:00, 18013.30it/s] 58%|█████▊ | 2885/5000 [4:11:17<8:47:28, 14.96s/it] 58%|█████▊ | 2886/5000 [4:11:21<6:49:56, 11.64s/it] 58%|█████▊ | 2887/5000 [4:11:25<5:27:51, 9.31s/it] 58%|█████▊ | 2888/5000 [4:11:29<4:30:15, 7.68s/it] 58%|█████▊ | 2889/5000 [4:11:33<3:59:55, 6.82s/it] 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Running Evaluation ***** [INFO|trainer.py:2959] 2023-07-20 15:25:19,810 >> Num examples: Unknown [INFO|trainer.py:2960] 2023-07-20 15:25:19,810 >> Batch size = 16 {'loss': 0.0052, 'learning_rate': 4.673333333333333e-06, 'epoch': 7.0} {'loss': 0.005, 'learning_rate': 4.617777777777778e-06, 'epoch': 7.01} {'loss': 0.0041, 'learning_rate': 4.562222222222222e-06, 'epoch': 7.01} {'loss': 0.0045, 'learning_rate': 4.506666666666667e-06, 'epoch': 7.02} {'loss': 0.0044, 'learning_rate': 4.451111111111112e-06, 'epoch': 7.02} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 1.64it/s] Reading metadata...: 6591it [00:00, 10445.80it/s] [INFO|trainer_utils.py:689] 2023-07-20 15:25:23,135 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. 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'learning_rate': 4.395555555555556e-06, 'epoch': 7.03} {'loss': 0.0041, 'learning_rate': 4.34e-06, 'epoch': 7.03} {'loss': 0.0035, 'learning_rate': 4.284444444444445e-06, 'epoch': 7.04} {'loss': 0.0044, 'learning_rate': 4.228888888888889e-06, 'epoch': 7.04} {'loss': 0.0039, 'learning_rate': 4.173333333333334e-06, 'epoch': 7.05} {'loss': 0.0031, 'learning_rate': 4.117777777777779e-06, 'epoch': 7.05} {'loss': 0.0032, 'learning_rate': 4.062222222222223e-06, 'epoch': 7.06} {'loss': 0.0034, 'learning_rate': 4.006666666666667e-06, 'epoch': 7.06} {'loss': 0.0028, 'learning_rate': 3.951111111111112e-06, 'epoch': 7.07} {'loss': 0.0032, 'learning_rate': 3.895555555555556e-06, 'epoch': 7.07} {'loss': 0.003, 'learning_rate': 3.8400000000000005e-06, 'epoch': 7.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.02it/s] Reading metadata...: 10918it [00:00, 20512.76it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 3.02it/s] Reading metadata...: 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3.5622222222222224e-06, 'epoch': 8.02} {'loss': 0.0029, 'learning_rate': 3.5066666666666673e-06, 'epoch': 8.03} {'loss': 0.0027, 'learning_rate': 3.4511111111111113e-06, 'epoch': 8.03} {'loss': 0.0022, 'learning_rate': 3.3955555555555558e-06, 'epoch': 8.04} {'loss': 0.0024, 'learning_rate': 3.3400000000000006e-06, 'epoch': 8.04} {'loss': 0.0028, 'learning_rate': 3.2844444444444447e-06, 'epoch': 8.05} {'loss': 0.0025, 'learning_rate': 3.228888888888889e-06, 'epoch': 8.05} {'loss': 0.0022, 'learning_rate': 3.173333333333334e-06, 'epoch': 8.06} {'loss': 0.0021, 'learning_rate': 3.117777777777778e-06, 'epoch': 8.06} {'loss': 0.002, 'learning_rate': 3.0622222222222225e-06, 'epoch': 8.07} {'loss': 0.0019, 'learning_rate': 3.0066666666666674e-06, 'epoch': 8.07} {'loss': 0.0019, 'learning_rate': 2.9511111111111114e-06, 'epoch': 8.08} {'loss': 0.0019, 'learning_rate': 2.895555555555556e-06, 'epoch': 8.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 1.99it/s] Reading metadata...: 10918it [00:00, 20239.67it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 3.18it/s] Reading metadata...: 6591it [00:00, 18951.45it/s] 74%|███████▍ | 3709/5000 [5:29:31<5:06:10, 14.23s/it] 74%|███████▍ | 3710/5000 [5:29:36<4:03:17, 11.32s/it] 74%|███████▍ | 3711/5000 [5:29:40<3:19:30, 9.29s/it] 74%|███████▍ | 3712/5000 [5:29:44<2:44:31, 7.66s/it] 74%|███████▍ | 3713/5000 [5:29:48<2:22:23, 6.64s/it] 74%|███████▍ | 3714/5000 [5:29:53<2:10:09, 6.07s/it] 74%|███████▍ | 3715/5000 [5:29:58<2:04:50, 5.83s/it] 74%|███████▍ | 3716/5000 [5:30:04<2:03:40, 5.78s/it] 74%|███████▍ | 3717/5000 [5:30:09<1:59:45, 5.60s/it] 74%|███████▍ | 3718/5000 [5:30:14<1:57:00, 5.48s/it] 74%|███████▍ | 3719/5000 [5:30:19<1:52:00, 5.25s/it] 74%|███████▍ | 3720/5000 [5:30:23<1:42:48, 4.82s/it] 74%|███████▍ | 3721/5000 [5:30:27<1:41:01, 4.74s/it] 74%|███████▍ | 3722/5000 [5:30:31<1:35:21, 4.48s/it] 74%|███████▍ | 3723/5000 [5:30:36<1:35:26, 4.48s/it] 74%|███████▍ | 3724/5000 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2.5622222222222226e-06, 'epoch': 9.03} {'loss': 0.0017, 'learning_rate': 2.5066666666666667e-06, 'epoch': 9.03} {'loss': 0.0018, 'learning_rate': 2.451111111111111e-06, 'epoch': 9.04} {'loss': 0.0017, 'learning_rate': 2.3955555555555556e-06, 'epoch': 9.04} {'loss': 0.002, 'learning_rate': 2.3400000000000005e-06, 'epoch': 9.05} {'loss': 0.0017, 'learning_rate': 2.2844444444444445e-06, 'epoch': 9.05} {'loss': 0.0016, 'learning_rate': 2.228888888888889e-06, 'epoch': 9.06} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 1.96it/s] Reading metadata...: 6591it [00:00, 12415.69it/s] [INFO|trainer_utils.py:689] 2023-07-20 16:56:44,381 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 80%|████████ | 4000/5000 [6:07:23<1:15:12, 4.51s/it][INFO|trainer.py:2700] 2023-07-20 17:12:49,858 >> Saving model checkpoint to ./checkpoint-4000 [INFO|configuration_utils.py:447] 2023-07-20 17:12:49,859 >> Configuration saved in ./checkpoint-4000/config.json [INFO|modeling_utils.py:1693] 2023-07-20 17:12:51,133 >> Model weights saved in ./checkpoint-4000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 17:12:51,145 >> Feature extractor saved in ./checkpoint-4000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2023-07-20 17:12:57,138 >> Feature extractor saved in ./preprocessor_config.json 80%|████████ | 4001/5000 [6:08:06<85:05:49, 306.66s/it] 80%|████████ | 4002/5000 [6:08:11<59:53:28, 216.04s/it] 80%|████████ | 4003/5000 [6:08:16<42:16:08, 152.63s/it] 80%|████████ | 4004/5000 [6:08:21<30:00:37, 108.47s/it] 80%|████████ | 4005/5000 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11.07} {'loss': 0.0012, 'learning_rate': 1.7333333333333335e-07, 'epoch': 11.08} Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.03it/s] Reading metadata...: 10918it [00:00, 20576.41it/s] Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 3.17it/s] Reading metadata...: 6591it [00:00, 19593.04it/s] 99%|█████████▉| 4945/5000 [7:19:57<14:26, 15.75s/it] 99%|█████████▉| 4946/5000 [7:20:01<10:57, 12.18s/it] 99%|█████████▉| 4947/5000 [7:20:05<08:32, 9.68s/it] 99%|█████████▉| 4948/5000 [7:20:09<06:55, 8.00s/it] 99%|█████████▉| 4949/5000 [7:20:13<05:55, 6.97s/it] 99%|█████████▉| 4950/5000 [7:20:19<05:33, 6.67s/it] 99%|█████████▉| 4950/5000 [7:20:19<05:33, 6.67s/it] 99%|█████████▉| 4951/5000 [7:20:24<05:02, 6.17s/it] 99%|█████████▉| 4952/5000 [7:20:29<04:34, 5.71s/it] 99%|█████████▉| 4953/5000 [7:20:33<04:01, 5.13s/it] 99%|█████████▉| 4954/5000 [7:20:37<03:38, 4.75s/it] 99%|█████████▉| 4955/5000 [7:20:40<03:21, 4.48s/it] 99%|█████████▉| 4956/5000 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6591it [00:00, 20693.01it/s] [INFO|trainer_utils.py:689] 2023-07-20 18:29:31,403 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 100%|██████████| 5000/5000 [7:40:15<00:00, 4.97s/it][INFO|trainer.py:2700] 2023-07-20 18:45:41,667 >> Saving model checkpoint to ./checkpoint-5000 [INFO|configuration_utils.py:447] 2023-07-20 18:45:41,667 >> Configuration saved in ./checkpoint-5000/config.json [INFO|modeling_utils.py:1693] 2023-07-20 18:45:42,938 >> Model weights saved in ./checkpoint-5000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 18:45:42,945 >> Feature extractor saved in ./checkpoint-5000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2023-07-20 18:45:48,327 >> Feature extractor saved in ./preprocessor_config.json [INFO|trainer.py:1892] 2023-07-20 18:46:19,265 >> Training completed. Do not forget to share your model on huggingface.co/models =) [INFO|trainer.py:2016] 2023-07-20 18:46:19,266 >> Loading best model from ./checkpoint-4000 (score: 18.775568066750374). 100%|██████████| 5000/5000 [7:40:53<00:00, 4.97s/it] 100%|██████████| 5000/5000 [7:40:53<00:00, 5.53s/it] [INFO|trainer.py:2700] 2023-07-20 18:46:19,691 >> Saving model checkpoint to ./ [INFO|configuration_utils.py:447] 2023-07-20 18:46:19,691 >> Configuration saved in ./config.json [INFO|modeling_utils.py:1693] 2023-07-20 18:46:21,329 >> Model weights saved in ./pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 18:46:21,341 >> Feature extractor saved in ./preprocessor_config.json [INFO|trainer.py:2700] 2023-07-20 18:46:21,342 >> Saving model checkpoint to ./ [INFO|configuration_utils.py:447] 2023-07-20 18:46:21,343 >> Configuration saved in ./config.json [INFO|modeling_utils.py:1693] 2023-07-20 18:46:22,695 >> Model weights saved in ./pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 18:46:22,710 >> Feature extractor saved in ./preprocessor_config.json Several commits (2) will be pushed upstream. {'eval_loss': 0.3913772702217102, 'eval_wer': 18.83024828871157, 'eval_runtime': 973.2149, 'eval_samples_per_second': 6.772, 'eval_steps_per_second': 0.423, 'epoch': 12.01} {'train_runtime': 27653.1068, 'train_samples_per_second': 5.786, 'train_steps_per_second': 0.181, 'train_loss': 0.106446673027426, 'epoch': 12.01} 07/20/2023 18:46:51 - WARNING - huggingface_hub.repository - Several commits (2) will be pushed upstream. The progress bars may be unreliable. 07/20/2023 18:46:51 - WARNING - huggingface_hub.repository - The progress bars may be unreliable. Upload file pytorch_model.bin: 0%| | 1.00/922M [00:00 main 07/20/2023 19:08:06 - WARNING - huggingface_hub.repository - To https://huggingface.co/xezpeleta/whisper-small-eu-v2 eb496bd..9ecd845 main -> main Upload file pytorch_model.bin: 100%|██████████| 922M/922M [21:13<00:00, 816kB/s] Upload file pytorch_model.bin: 100%|██████████| 922M/922M [21:13<00:00, 759kB/s] Upload file runs/Jul20_11-05-05_tknadmin-System-Product-Name/events.out.tfevents.1689843926.tknadmin-System-Product-Name.2399.0: 100%|██████████| 36.7k/36.7k [21:13<00:00, 16.0MB/s] Upload file runs/Jul20_11-05-05_tknadmin-System-Product-Name/events.out.tfevents.1689843926.tknadmin-System-Product-Name.2399.0: 100%|██████████| 36.7k/36.7k [21:13<00:00, 29.5B/s] To https://huggingface.co/xezpeleta/whisper-small-eu-v2 9ecd845..6d7e844 main -> main 07/20/2023 19:08:10 - WARNING - huggingface_hub.repository - To https://huggingface.co/xezpeleta/whisper-small-eu-v2 9ecd845..6d7e844 main -> main ***** train metrics ***** epoch = 12.01 train_loss = 0.1064 train_runtime = 7:40:53.10 train_samples_per_second = 5.786 train_steps_per_second = 0.181 07/20/2023 19:08:13 - INFO - __main__ - *** Evaluate *** [INFO|trainer.py:2955] 2023-07-20 19:08:13,052 >> ***** Running Evaluation ***** [INFO|trainer.py:2959] 2023-07-20 19:08:13,052 >> Num examples: Unknown [INFO|trainer.py:2960] 2023-07-20 19:08:13,052 >> Batch size = 16 Reading metadata...: 0it [00:00, ?it/s] Reading metadata...: 1it [00:00, 2.82it/s] Reading metadata...: 6591it [00:00, 16978.63it/s] [INFO|trainer_utils.py:689] 2023-07-20 19:08:16,031 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. [INFO|trainer.py:2700] 2023-07-20 19:24:05,011 >> Saving model checkpoint to ./ [INFO|configuration_utils.py:447] 2023-07-20 19:24:05,011 >> Configuration saved in ./config.json [INFO|modeling_utils.py:1693] 2023-07-20 19:24:06,334 >> Model weights saved in ./pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2023-07-20 19:24:06,347 >> Feature extractor saved in ./preprocessor_config.json ***** eval metrics ***** epoch = 12.01 eval_loss = 0.3812 eval_runtime = 0:15:51.95 eval_samples_per_second = 6.924 eval_steps_per_second = 0.433 eval_wer = 18.7756 Upload file runs/Jul20_11-05-05_tknadmin-System-Product-Name/events.out.tfevents.1689873845.tknadmin-System-Product-Name.2399.2: 100%|██████████| 358/358 [00:00 main 07/20/2023 19:24:13 - WARNING - huggingface_hub.repository - To https://huggingface.co/xezpeleta/whisper-small-eu-v2 6d7e844..53e38ec main -> main Upload file runs/Jul20_11-05-05_tknadmin-System-Product-Name/events.out.tfevents.1689873845.tknadmin-System-Product-Name.2399.2: 100%|██████████| 358/358 [00:01