12/12/2022 13:35:10 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True 12/12/2022 13:35:10 - 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=None, 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-06, length_column_name=input_length, load_best_model_at_end=False, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Dec12_13-35-10_129-146-55-28, 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=None, 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=200, weight_decay=0.0, xpu_backend=None, ) 12/12/2022 13:35:10 - 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=None, 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-06, length_column_name=input_length, load_best_model_at_end=False, local_rank=-1, log_level=passive, log_level_replica=passive, log_on_each_node=True, logging_dir=./runs/Dec12_13-35-10_129-146-55-28, 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=None, 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=200, weight_decay=0.0, xpu_backend=None, ) 12/12/2022 13:35:12 - WARNING - datasets.builder - Using custom data configuration zeynepgulhan--mediaspeech-with-cv-tr-5f4b6cf5ea082abc 12/12/2022 13:35:13 - WARNING - datasets.builder - Using custom data configuration zeynepgulhan--mediaspeech-with-cv-tr-5f4b6cf5ea082abc [INFO|configuration_utils.py:654] 2022-12-12 13:35:13,635 >> loading configuration file config.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/config.json [INFO|configuration_utils.py:706] 2022-12-12 13:35:13,638 >> Model config WhisperConfig { "_name_or_path": "openai/whisper-medium", "activation_dropout": 0.0, "activation_function": "gelu", "architectures": [ "WhisperForConditionalGeneration" ], "attention_dropout": 0.0, "begin_suppress_tokens": [ 220, 50257 ], "bos_token_id": 50257, "d_model": 1024, "decoder_attention_heads": 16, "decoder_ffn_dim": 4096, "decoder_layerdrop": 0.0, "decoder_layers": 24, "decoder_start_token_id": 50258, "dropout": 0.0, "encoder_attention_heads": 16, "encoder_ffn_dim": 4096, "encoder_layerdrop": 0.0, "encoder_layers": 24, "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": 24, "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] 2022-12-12 13:35:13,878 >> loading configuration file preprocessor_config.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/preprocessor_config.json [INFO|feature_extraction_utils.py:501] 2022-12-12 13:35:13,893 >> 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, 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[INFO|tokenization_utils_base.py:1799] 2022-12-12 13:35:14,132 >> loading file merges.txt from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/merges.txt [INFO|tokenization_utils_base.py:1799] 2022-12-12 13:35:14,132 >> loading file normalizer.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/normalizer.json [INFO|tokenization_utils_base.py:1799] 2022-12-12 13:35:14,132 >> loading file added_tokens.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/added_tokens.json [INFO|tokenization_utils_base.py:1799] 2022-12-12 13:35:14,132 >> loading file special_tokens_map.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/special_tokens_map.json [INFO|tokenization_utils_base.py:1799] 2022-12-12 13:35:14,132 >> loading file tokenizer_config.json from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/tokenizer_config.json [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|endoftext|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|startoftranscript|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|en|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|zh|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|de|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|es|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|ru|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|ko|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|fr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|ja|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|pt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|tr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|pl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|ca|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|nl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|ar|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|sv|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|it|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|id|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|hi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|fi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|vi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|iw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,192 >> Adding <|uk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|el|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ms|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|cs|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ro|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|da|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|hu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ta|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|no|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|th|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ur|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|hr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|bg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|lt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|la|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|mi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ml|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|cy|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|sk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|te|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|fa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|lv|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|bn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|sr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|az|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|sl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|kn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|et|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|mk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|br|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|eu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|is|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|hy|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|ne|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|mn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|bs|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|kk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|sq|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,193 >> Adding <|sw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|gl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|mr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|pa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|si|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|km|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|sn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|yo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|so|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|af|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|oc|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ka|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|be|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|tg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|sd|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|gu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|am|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|yi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|lo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|uz|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|fo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ht|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ps|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|tk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|nn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|mt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|sa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|lb|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|my|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|bo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|tl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|mg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|as|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|tt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|haw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ln|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ha|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,194 >> Adding <|ba|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|jw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|su|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|translate|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|transcribe|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|startoflm|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|startofprev|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|nocaptions|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:14,195 >> Adding <|notimestamps|> to the vocabulary [INFO|modeling_utils.py:2238] 2022-12-12 13:35:14,198 >> loading weights file pytorch_model.bin from cache at /home/ubuntu/.cache/huggingface/hub/models--openai--whisper-medium/snapshots/a0b3589e1034234495a1b696c28d4832cdaf8a32/pytorch_model.bin [INFO|modeling_utils.py:2742] 2022-12-12 13:35:22,642 >> All model checkpoint weights were used when initializing WhisperForConditionalGeneration. [INFO|modeling_utils.py:2750] 2022-12-12 13:35:22,642 >> All the weights of WhisperForConditionalGeneration were initialized from the model checkpoint at openai/whisper-medium. 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. [INFO|feature_extraction_utils.py:368] 2022-12-12 13:35:23,314 >> Feature extractor saved in ./preprocessor_config.json [INFO|tokenization_utils_base.py:2157] 2022-12-12 13:35:23,315 >> tokenizer config file saved in ./tokenizer_config.json [INFO|tokenization_utils_base.py:2164] 2022-12-12 13:35:23,315 >> Special tokens file saved in ./special_tokens_map.json [INFO|tokenization_utils_base.py:2210] 2022-12-12 13:35:23,315 >> added tokens file saved in ./added_tokens.json [INFO|configuration_utils.py:447] 2022-12-12 13:35:23,397 >> Configuration saved in ./config.json [INFO|image_processing_utils.py:294] 2022-12-12 13:35:23,399 >> loading configuration file ./preprocessor_config.json [INFO|feature_extraction_utils.py:462] 2022-12-12 13:35:23,405 >> loading configuration file ./preprocessor_config.json [INFO|feature_extraction_utils.py:501] 2022-12-12 13:35:23,420 >> 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, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 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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2022-12-12 13:35:23,421 >> loading file vocab.json [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file tokenizer.json [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file merges.txt [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file normalizer.json [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file added_tokens.json [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file special_tokens_map.json [INFO|tokenization_utils_base.py:1797] 2022-12-12 13:35:23,421 >> loading file tokenizer_config.json [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|endoftext|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|startoftranscript|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|en|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|zh|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|de|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|es|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ru|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ko|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|fr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ja|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|pt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|tr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|pl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ca|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|nl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ar|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|sv|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|it|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|id|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|hi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|fi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|vi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|iw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|uk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|el|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ms|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|cs|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ro|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|da|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|hu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|ta|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,478 >> Adding <|no|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|th|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|ur|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|hr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|bg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|lt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|la|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|mi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|ml|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|cy|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|te|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|fa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|lv|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|bn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|az|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|kn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|et|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|mk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|br|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|eu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|is|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|hy|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|ne|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|mn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|bs|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|kk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sq|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|gl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|mr|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|pa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|si|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|km|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|sn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,479 >> Adding <|yo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|so|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|af|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|oc|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ka|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|be|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|tg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|sd|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|gu|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|am|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|yi|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|lo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|uz|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|fo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ht|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ps|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|tk|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|nn|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|mt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|sa|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|lb|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|my|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|bo|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|tl|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|mg|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|as|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|tt|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|haw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ln|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ha|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|ba|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|jw|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|su|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|translate|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|transcribe|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,480 >> Adding <|startoflm|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,481 >> Adding <|startofprev|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,481 >> Adding <|nocaptions|> to the vocabulary [INFO|tokenization_utils.py:426] 2022-12-12 13:35:23,481 >> Adding <|notimestamps|> to the vocabulary /home/ubuntu/whisper-mediaspeech-cv-tr-v2/./ is already a clone of https://huggingface.co/zeynepgulhan/whisper-mediaspeech-cv-tr-v2. Make sure you pull the latest changes with `repo.git_pull()`. 12/12/2022 13:35:25 - WARNING - huggingface_hub.repository - /home/ubuntu/whisper-mediaspeech-cv-tr-v2/./ is already a clone of https://huggingface.co/zeynepgulhan/whisper-mediaspeech-cv-tr-v2. Make sure you pull the latest changes with `repo.git_pull()`. [INFO|trainer.py:511] 2022-12-12 13:35:28,033 >> max_steps is given, it will override any value given in num_train_epochs [INFO|trainer.py:565] 2022-12-12 13:35:28,034 >> Using cuda_amp half precision backend /home/ubuntu/hf_env/lib/python3.8/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:1642] 2022-12-12 13:35:28,055 >> ***** Running training ***** [INFO|trainer.py:1643] 2022-12-12 13:35:28,055 >> Num examples = 160000 [INFO|trainer.py:1644] 2022-12-12 13:35:28,055 >> Num Epochs = 9223372036854775807 [INFO|trainer.py:1645] 2022-12-12 13:35:28,055 >> Instantaneous batch size per device = 32 [INFO|trainer.py:1646] 2022-12-12 13:35:28,055 >> Total train batch size (w. parallel, distributed & accumulation) = 32 [INFO|trainer.py:1647] 2022-12-12 13:35:28,055 >> Gradient Accumulation steps = 1 [INFO|trainer.py:1648] 2022-12-12 13:35:28,055 >> Total optimization steps = 5000 [INFO|trainer.py:1649] 2022-12-12 13:35:28,057 >> Number of trainable parameters = 763857920 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 [00:41<57:54:07, 41.70s/it] 0%| | 2/5000 [00:46<27:58:36, 20.15s/it] 0%| | 3/5000 [00:51<18:27:52, 13.30s/it] 0%| | 4/5000 [00:57<14:02:27, 10.12s/it] 0%| | 5/5000 [01:03<11:55:32, 8.60s/it] 0%| | 6/5000 [01:08<10:15:51, 7.40s/it] 0%| | 7/5000 [01:13<9:14:36, 6.66s/it] 0%| | 8/5000 [01:18<8:35:30, 6.20s/it] 0%| | 9/5000 [01:23<8:11:38, 5.91s/it] 0%| | 10/5000 [01:30<8:33:08, 6.17s/it] 0%| | 11/5000 [01:36<8:30:18, 6.14s/it] 0%| | 12/5000 [01:41<8:06:52, 5.86s/it] 0%| | 13/5000 [01:47<8:12:16, 5.92s/it] 0%| | 14/5000 [01:53<7:57:21, 5.74s/it] 0%| | 15/5000 [01:58<7:41:58, 5.56s/it] 0%| | 16/5000 [02:03<7:31:53, 5.44s/it] 0%| | 17/5000 [02:08<7:24:10, 5.35s/it] 0%| | 18/5000 [02:13<7:20:47, 5.31s/it] 0%| | 19/5000 [02:18<7:15:09, 5.24s/it] 0%| | 20/5000 [02:24<7:14:28, 5.23s/it] 0%| | 21/5000 [02:29<7:12:56, 5.22s/it] 0%| | 22/5000 [02:35<7:37:36, 5.52s/it] 0%| 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If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 20%|██ | 1000/5000 [3:09:28<5:54:23, 5.32s/it][INFO|trainer.py:2701] 2022-12-12 16:44:56,805 >> Saving model checkpoint to ./checkpoint-1000 [INFO|configuration_utils.py:447] 2022-12-12 16:44:56,806 >> Configuration saved in ./checkpoint-1000/config.json [INFO|modeling_utils.py:1671] 2022-12-12 16:44:59,359 >> Model weights saved in ./checkpoint-1000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2022-12-12 16:44:59,373 >> Feature extractor saved in ./checkpoint-1000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2022-12-12 16:45:05,874 >> Feature extractor saved in ./preprocessor_config.json 20%|██ | 1001/5000 [3:10:06<1930:10:01, 1737.58s/it] 20%|██ | 1002/5000 [3:10:14<1353:19:47, 1218.61s/it] 20%|██ | 1003/5000 [3:10:21<949:19:16, 855.03s/it] 20%|██ | 1004/5000 [3:10:27<666:19:18, 600.29s/it] 20%|██ | 1005/5000 [3:10:33<468:15:44, 421.96s/it] 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[4:42:22<4:39:07, 5.57s/it] 40%|███▉ | 1996/5000 [4:42:29<4:53:51, 5.87s/it] 40%|███▉ | 1997/5000 [4:42:34<4:44:25, 5.68s/it] 40%|███▉ | 1998/5000 [4:42:39<4:36:50, 5.53s/it] 40%|███▉ | 1999/5000 [4:42:45<4:32:04, 5.44s/it] 40%|████ | 2000/5000 [4:42:50<4:26:51, 5.34s/it] 40%|████ | 2000/5000 [4:42:50<4:26:51, 5.34s/it][INFO|trainer.py:2956] 2022-12-12 18:18:18,193 >> ***** Running Evaluation ***** [INFO|trainer.py:2960] 2022-12-12 18:18:18,193 >> Num examples: Unknown [INFO|trainer.py:2961] 2022-12-12 18:18:18,193 >> Batch size = 16 [INFO|trainer_utils.py:689] 2022-12-12 18:18:33,012 >> 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 [6:18:14<4:26:51, 5.34s/it][INFO|trainer.py:2701] 2022-12-12 19:53:42,501 >> Saving model checkpoint to ./checkpoint-2000 [INFO|configuration_utils.py:447] 2022-12-12 19:53:42,502 >> Configuration saved in ./checkpoint-2000/config.json [INFO|modeling_utils.py:1671] 2022-12-12 19:53:45,040 >> Model weights saved in ./checkpoint-2000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2022-12-12 19:53:45,054 >> Feature extractor saved in ./checkpoint-2000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2022-12-12 19:53:54,909 >> Feature extractor saved in ./preprocessor_config.json Adding files tracked by Git LFS: ['.training.log.swp']. 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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. 60%|██████ | 3000/5000 [9:28:44<3:05:59, 5.58s/it][INFO|trainer.py:2701] 2022-12-12 23:04:12,218 >> Saving model checkpoint to ./checkpoint-3000 [INFO|configuration_utils.py:447] 2022-12-12 23:04:12,219 >> Configuration saved in ./checkpoint-3000/config.json [INFO|modeling_utils.py:1671] 2022-12-12 23:04:14,766 >> Model weights saved in ./checkpoint-3000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2022-12-12 23:04:14,781 >> Feature extractor saved in ./checkpoint-3000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2022-12-12 23:04:24,354 >> Feature extractor saved in ./preprocessor_config.json 60%|██████ | 3001/5000 [9:30:31<975:50:39, 1757.40s/it] 60%|██████ | 3002/5000 [9:30:38<683:55:37, 1232.30s/it] 60%|██████ | 3003/5000 [9:30:44<479:31:43, 864.45s/it] 60%|██████ | 3004/5000 [9:30:52<336:47:03, 607.43s/it] 60%|██████ | 3005/5000 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If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message. 80%|████████ | 4000/5000 [12:39:03<1:28:14, 5.29s/it][INFO|trainer.py:2701] 2022-12-13 02:14:31,582 >> Saving model checkpoint to ./checkpoint-4000 [INFO|configuration_utils.py:447] 2022-12-13 02:14:31,583 >> Configuration saved in ./checkpoint-4000/config.json [INFO|modeling_utils.py:1671] 2022-12-13 02:14:34,137 >> Model weights saved in ./checkpoint-4000/pytorch_model.bin [INFO|feature_extraction_utils.py:368] 2022-12-13 02:14:34,152 >> Feature extractor saved in ./checkpoint-4000/preprocessor_config.json [INFO|feature_extraction_utils.py:368] 2022-12-13 02:14:44,618 >> Feature extractor saved in ./preprocessor_config.json