whisper-small-es / training.log

Training in progress, step 1000

7a36179 over 1 year ago

105 kB

	05/10/2023 09:41:07 - WARNING - __main__ - Process rank: 0, device: cuda:0, n_gpu: 2distributed training: True, 16-bits training: True
	05/10/2023 09:41:07 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments(
	_n_gpu=2,
	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_backend=None,
	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_config={'fsdp_min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},
	fsdp_min_num_params=0,
	fsdp_transformer_layer_cls_to_wrap=None,
	full_determinism=False,
	generation_config=None,
	generation_max_length=225,
	generation_num_beams=None,
	gradient_accumulation_steps=2,
	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=<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=0,
	log_level=passive,
	log_level_replica=warning,
	log_on_each_node=True,
	logging_dir=./runs/May10_09-41-06_crimv3mgpu016,
	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=32,
	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=<PUSH_TO_HUB_TOKEN>,
	ray_scope=last,
	remove_unused_columns=True,
	report_to=['wandb'],
	resume_from_checkpoint=None,
	run_name=./,
	save_on_each_node=False,
	save_safetensors=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,
	)
	05/10/2023 09:41:07 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments(
	_n_gpu=2,
	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_backend=None,
	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_config={'fsdp_min_num_params': 0, 'xla': False, 'xla_fsdp_grad_ckpt': False},
	fsdp_min_num_params=0,
	fsdp_transformer_layer_cls_to_wrap=None,
	full_determinism=False,
	generation_config=None,
	generation_max_length=225,
	generation_num_beams=None,
	gradient_accumulation_steps=2,
	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=<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=0,
	log_level=passive,
	log_level_replica=warning,
	log_on_each_node=True,
	logging_dir=./runs/May10_09-41-06_crimv3mgpu016,
	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=32,
	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=<PUSH_TO_HUB_TOKEN>,
	ray_scope=last,
	remove_unused_columns=True,
	report_to=['wandb'],
	resume_from_checkpoint=None,
	run_name=./,
	save_on_each_node=False,
	save_safetensors=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,
	)
	[INFO\|configuration_utils.py:669] 2023-05-10 09:41:19,641 >> loading configuration file config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/config.json
	[INFO\|configuration_utils.py:725] 2023-05-10 09:41:19,653 >> Model config WhisperConfig {
	"_name_or_path": "openai/whisper-small",
	"activation_dropout": 0.0,
	"activation_function": "gelu",
	"apply_spec_augment": false,
	"architectures": [
	"WhisperForConditionalGeneration"
	],
	"attention_dropout": 0.0,
	"begin_suppress_tokens": [
	220,
	50257
	],
	"bos_token_id": 50257,
	"classifier_proj_size": 256,
	"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,
	"mask_feature_length": 10,
	"mask_feature_min_masks": 0,
	"mask_feature_prob": 0.0,
	"mask_time_length": 10,
	"mask_time_min_masks": 2,
	"mask_time_prob": 0.05,
	"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,
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	59,
	60,
	61,
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	6585,
	6647,
	7273,
	9061,
	9383,
	10428,
	10929,
	11938,
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	12331,
	12562,
	13793,
	14157,
	14635,
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	18956,
	20075,
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	22520,
	26130,
	26161,
	26435,
	28279,
	29464,
	31650,
	32302,
	32470,
	36865,
	42863,
	47425,
	49870,
	50254,
	50258,
	50360,
	50361,
	50362
	],
	"torch_dtype": "float32",
	"transformers_version": "4.29.0.dev0",
	"use_cache": true,
	"use_weighted_layer_sum": false,
	"vocab_size": 51865
	}

	[INFO\|feature_extraction_utils.py:469] 2023-05-10 09:41:19,843 >> loading configuration file preprocessor_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/preprocessor_config.json
	[INFO\|feature_extraction_utils.py:511] 2023-05-10 09:41:19,849 >> Feature extractor WhisperFeatureExtractor {
	"chunk_length": 30,
	"feature_extractor_type": "WhisperFeatureExtractor",
	"feature_size": 80,
	"hop_length": 160,
	"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
	}

	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file vocab.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/vocab.json
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file tokenizer.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/tokenizer.json
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file merges.txt from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/merges.txt
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file normalizer.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/normalizer.json
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file added_tokens.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/added_tokens.json
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file special_tokens_map.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/special_tokens_map.json
	[INFO\|tokenization_utils_base.py:1810] 2023-05-10 09:41:20,054 >> loading file tokenizer_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/tokenizer_config.json
	[INFO\|modeling_utils.py:2542] 2023-05-10 09:41:20,144 >> loading weights file pytorch_model.bin from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/pytorch_model.bin
	[INFO\|configuration_utils.py:577] 2023-05-10 09:41:20,754 >> Generate config GenerationConfig {
	"_from_model_config": true,
	"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": "4.29.0.dev0",
	"use_cache": false
	}

	[INFO\|modeling_utils.py:3211] 2023-05-10 09:41:23,296 >> All model checkpoint weights were used when initializing WhisperForConditionalGeneration.

	[INFO\|modeling_utils.py:3219] 2023-05-10 09:41:23,296 >> 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.
	[INFO\|configuration_utils.py:539] 2023-05-10 09:41:23,501 >> loading configuration file generation_config.json from cache at /home/local/QCRI/dizham/.cache/huggingface/hub/models--openai--whisper-small/snapshots/f6744499d1eba717bcf4d6be735e3d386ffb60ad/generation_config.json
	[INFO\|configuration_utils.py:577] 2023-05-10 09:41:23,502 >> 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
	]
	],
	"is_multilingual": true,
	"lang_to_id": {
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	"<\|yo\|>": 50325,
	"<\|zh\|>": 50260
	},
	"max_initial_timestamp_index": 1,
	"max_length": 448,
	"no_timestamps_token_id": 50363,
	"pad_token_id": 50257,
	"return_timestamps": false,
	"suppress_tokens": [
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	"task_to_id": {
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	"transformers_version": "4.29.0.dev0"
	}

	[INFO\|feature_extraction_utils.py:369] 2023-05-10 09:41:24,661 >> Feature extractor saved in ./preprocessor_config.json
	[INFO\|tokenization_utils_base.py:2181] 2023-05-10 09:41:24,666 >> tokenizer config file saved in ./tokenizer_config.json
	[INFO\|tokenization_utils_base.py:2188] 2023-05-10 09:41:24,671 >> Special tokens file saved in ./special_tokens_map.json
	[INFO\|configuration_utils.py:458] 2023-05-10 09:41:24,826 >> Configuration saved in ./config.json
	[INFO\|image_processing_utils.py:307] 2023-05-10 09:41:24,827 >> loading configuration file ./preprocessor_config.json
	[INFO\|feature_extraction_utils.py:467] 2023-05-10 09:41:24,834 >> loading configuration file ./preprocessor_config.json
	[INFO\|feature_extraction_utils.py:511] 2023-05-10 09:41:24,835 >> Feature extractor WhisperFeatureExtractor {
	"chunk_length": 30,
	"feature_extractor_type": "WhisperFeatureExtractor",
	"feature_size": 80,
	"hop_length": 160,
	"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
	}

	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file vocab.json
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file tokenizer.json
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file merges.txt
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file normalizer.json
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file added_tokens.json
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file special_tokens_map.json
	[INFO\|tokenization_utils_base.py:1808] 2023-05-10 09:41:24,836 >> loading file tokenizer_config.json
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|startoftranscript\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|en\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|zh\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|de\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|es\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ru\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ko\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|fr\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ja\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|pt\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|tr\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|pl\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ca\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|nl\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ar\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|sv\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|it\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|id\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|hi\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|fi\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|vi\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|he\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|uk\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|el\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ms\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|cs\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ro\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|da\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|hu\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|ta\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|no\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,898 >> Adding <\|th\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|ur\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|hr\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|bg\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|lt\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|la\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|mi\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|ml\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|cy\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sk\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|te\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|fa\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|lv\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|bn\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sr\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|az\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sl\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|kn\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|et\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|mk\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|br\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|eu\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|is\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|hy\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|ne\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|mn\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|bs\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|kk\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sq\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sw\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|gl\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|mr\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|pa\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|si\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|km\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|sn\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|yo\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|so\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|af\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|oc\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|ka\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|be\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,899 >> Adding <\|tg\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|sd\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|gu\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|am\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|yi\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|lo\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|uz\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|fo\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|ht\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|ps\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|tk\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|nn\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|mt\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|sa\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|lb\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|my\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|bo\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|tl\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|mg\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|as\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|tt\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|haw\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|ln\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|ha\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|ba\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|jw\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|su\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|translate\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|transcribe\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|startoflm\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|startofprev\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|nocaptions\|> to the vocabulary
	[INFO\|tokenization_utils.py:426] 2023-05-10 09:41:24,900 >> Adding <\|notimestamps\|> to the vocabulary
	/home/local/QCRI/dizham/kanari/whisper/whisper-small-es/./ is already a clone of https://huggingface.co/danielizham/whisper-small-es. Make sure you pull the latest changes with `repo.git_pull()`.
	05/10/2023 09:41:27 - WARNING - huggingface_hub.repository - /home/local/QCRI/dizham/kanari/whisper/whisper-small-es/./ is already a clone of https://huggingface.co/danielizham/whisper-small-es. Make sure you pull the latest changes with `repo.git_pull()`.
	[INFO\|trainer.py:565] 2023-05-10 09:41:30,128 >> max_steps is given, it will override any value given in num_train_epochs
	[INFO\|trainer.py:622] 2023-05-10 09:41:30,129 >> Using cuda_amp half precision backend
	/home/local/QCRI/dizham/miniconda3/envs/whisper/lib/python3.9/site-packages/transformers/optimization.py:407: 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:1771] 2023-05-10 09:41:30,142 >> *** Running training ***
	[INFO\|trainer.py:1772] 2023-05-10 09:41:30,142 >> Num examples = 640,000
	[INFO\|trainer.py:1773] 2023-05-10 09:41:30,142 >> Num Epochs = 9,223,372,036,854,775,807
	[INFO\|trainer.py:1774] 2023-05-10 09:41:30,142 >> Instantaneous batch size per device = 32
	[INFO\|trainer.py:1775] 2023-05-10 09:41:30,142 >> Total train batch size (w. parallel, distributed & accumulation) = 128
	[INFO\|trainer.py:1776] 2023-05-10 09:41:30,142 >> Gradient Accumulation steps = 2
	[INFO\|trainer.py:1777] 2023-05-10 09:41:30,142 >> Total optimization steps = 5,000
	[INFO\|trainer.py:1778] 2023-05-10 09:41:30,143 >> Number of trainable parameters = 241,734,912
	[INFO\|integrations.py:720] 2023-05-10 09:41:30,144 >> Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"
	wandb: Currently logged in as: danielizham. Use `wandb login --relogin` to force relogin
	wandb: Tracking run with wandb version 0.15.2
	wandb: Run data is saved locally in /home/local/QCRI/dizham/kanari/whisper/whisper-small-es/wandb/run-20230510_094132-lvsln7ks
	wandb: Run `wandb offline` to turn off syncing.
	wandb: Syncing run astral-silence-4
	wandb: ⭐️ View project at https://wandb.ai/danielizham/huggingface
	wandb: 🚀 View run at https://wandb.ai/danielizham/huggingface/runs/lvsln7ks
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	[INFO\|trainer_utils.py:693] 2023-05-10 09:43:41,176 >> 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.
	/home/local/QCRI/dizham/miniconda3/envs/whisper/lib/python3.9/site-packages/torch/nn/parallel/_functions.py:68: UserWarning: Was asked to gather along dimension 0, but all input tensors were scalars; will instead unsqueeze and return a vector.
	warnings.warn('Was asked to gather along dimension 0, but all '
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229/5000 [1:53:20<38:32:47, 29.09s/it] 5%\|▍ \| 230/5000 [1:53:52<39:21:26, 29.70s/it] 5%\|▍ \| 231/5000 [1:54:21<39:22:20, 29.72s/it] 5%\|▍ \| 232/5000 [1:54:48<38:19:35, 28.94s/it] 5%\|▍ \| 233/5000 [1:55:21<39:38:40, 29.94s/it] 5%\|▍ \| 234/5000 [1:55:48<38:32:29, 29.11s/it] 5%\|▍ \| 235/5000 [1:56:17<38:35:33, 29.16s/it] 5%\|▍ \| 236/5000 [1:56:47<38:48:54, 29.33s/it] 5%\|▍ \| 237/5000 [1:57:16<38:51:52, 29.37s/it] 5%\|▍ \| 238/5000 [1:57:47<39:14:27, 29.67s/it] 5%\|▍ \| 239/5000 [1:58:09<36:24:34, 27.53s/it] 5%\|▍ \| 240/5000 [1:58:20<29:42:14, 22.47s/it] 5%\|▍ \| 241/5000 [1:58:30<24:56:47, 18.87s/it] 5%\|▍ \| 242/5000 [1:58:41<21:36:39, 16.35s/it]{'loss': 1.0543, 'learning_rate': 4.800000000000001e-07, 'epoch': 0.01}
	{'loss': 0.8847, 'learning_rate': 9.800000000000001e-07, 'epoch': 0.01}
	{'loss': 0.54, 'learning_rate': 1.48e-06, 'epoch': 0.01}
	{'loss': 0.304, 'learning_rate': 1.98e-06, 'epoch': 0.02}
	{'loss': 0.2861, 'learning_rate': 2.4800000000000004e-06, 'epoch': 0.03}
	{'loss': 0.2395, 'learning_rate': 2.9800000000000003e-06, 'epoch': 0.03}
	{'loss': 0.2282, 'learning_rate': 3.48e-06, 'epoch': 0.04}
	{'loss': 0.2209, 'learning_rate': 3.980000000000001e-06, 'epoch': 0.04}
	{'loss': 0.2299, 'learning_rate': 4.48e-06, 'epoch': 0.04}

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	Reading metadata...: 229844it [00:24, 23238.20it/s][A Reading metadata...: 230467it [00:24, 9256.50it/s]

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28.65s/it] 10%\|▉ \| 482/5000 [3:55:41<29:43:37, 23.69s/it] 10%\|▉ \| 483/5000 [3:55:52<24:44:48, 19.72s/it] 10%\|▉ \| 484/5000 [3:56:02<21:16:03, 16.95s/it] 10%\|▉ \| 485/5000 [3:56:13<18:50:40, 15.03s/it]{'loss': 0.2867, 'learning_rate': 4.980000000000001e-06, 'epoch': 1.0}
	{'loss': 0.3646, 'learning_rate': 5.480000000000001e-06, 'epoch': 1.01}
	{'loss': 0.3278, 'learning_rate': 5.98e-06, 'epoch': 1.01}
	{'loss': 0.3748, 'learning_rate': 6.480000000000001e-06, 'epoch': 1.02}
	{'loss': 0.2737, 'learning_rate': 6.98e-06, 'epoch': 1.02}
	{'loss': 0.2653, 'learning_rate': 7.48e-06, 'epoch': 1.03}
	{'loss': 0.2596, 'learning_rate': 7.980000000000002e-06, 'epoch': 1.03}
	{'loss': 0.2665, 'learning_rate': 8.48e-06, 'epoch': 1.04}
	{'loss': 0.2598, 'learning_rate': 8.98e-06, 'epoch': 1.04}
	{'loss': 0.242, 'learning_rate': 9.48e-06, 'epoch': 1.05}

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	{'loss': 0.2256, 'learning_rate': 9.946666666666667e-06, 'epoch': 2.01}
	{'loss': 0.209, 'learning_rate': 9.891111111111113e-06, 'epoch': 2.01}
	05/10/2023 14:21:14 - WARNING - datasets.download.streaming_download_manager - Got disconnected from remote data host. Retrying in 5sec [1/20]
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15%\|█▍ \| 726/5000 [5:51:37<21:34:55, 18.18s/it] 15%\|█▍ \| 727/5000 [5:51:48<18:50:29, 15.87s/it]{'loss': 0.2339, 'learning_rate': 9.835555555555556e-06, 'epoch': 2.02}
	{'loss': 0.1714, 'learning_rate': 9.780000000000001e-06, 'epoch': 2.02}
	{'loss': 0.1657, 'learning_rate': 9.724444444444445e-06, 'epoch': 2.03}
	{'loss': 0.1688, 'learning_rate': 9.66888888888889e-06, 'epoch': 2.03}
	{'loss': 0.1616, 'learning_rate': 9.613333333333335e-06, 'epoch': 2.04}
	{'loss': 0.1541, 'learning_rate': 9.557777777777777e-06, 'epoch': 2.04}
	{'loss': 0.1565, 'learning_rate': 9.502222222222223e-06, 'epoch': 2.05}

	Reading metadata...: 0it [00:00, ?it/s][A
	Reading metadata...: 1it [00:00, 1.22it/s][A
	Reading metadata...: 15305it [00:00, 22720.16it/s][A
	Reading metadata...: 24307it [00:01, 16290.58it/s][A
	Reading metadata...: 38794it [00:01, 29865.72it/s][A
	Reading metadata...: 47811it [00:02, 24797.60it/s][A
	Reading metadata...: 59039it [00:03, 18295.04it/s][A
	Reading metadata...: 72636it [00:03, 27336.81it/s][A
	Reading metadata...: 80216it [00:04, 16069.94it/s][A
	Reading metadata...: 93450it [00:04, 23744.46it/s][A
	Reading metadata...: 101289it [00:04, 23211.42it/s][A
	Reading metadata...: 114047it [00:07, 10528.73it/s][A
	Reading metadata...: 128225it [00:07, 15810.54it/s][A
	Reading metadata...: 135590it [00:11, 5740.60it/s] [A
	Reading metadata...: 149664it [00:12, 8135.61it/s][A
	Reading metadata...: 164652it [00:12, 12291.18it/s][A
	Reading metadata...: 172319it [00:14, 7862.68it/s] [A
	Reading metadata...: 184380it [00:16, 6816.06it/s][A
	Reading metadata...: 199539it [00:16, 10435.79it/s][A
	Reading metadata...: 206876it [00:17, 11503.04it/s][A
	Reading metadata...: 220924it [00:17, 17051.73it/s][A
	Reading metadata...: 229142it [00:21, 5822.80it/s] [A Reading metadata...: 230467it [00:21, 10480.94it/s]

	Reading metadata...: 0it [00:00, ?it/s][A
	Reading metadata...: 1it [00:00, 3.29it/s][A
	Reading metadata...: 14712it [00:00, 47049.80it/s][A Reading metadata...: 15520it [00:00, 37871.82it/s]
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	{'loss': 0.1286, 'learning_rate': 9.335555555555557e-06, 'epoch': 3.01}
	{'loss': 0.1343, 'learning_rate': 9.280000000000001e-06, 'epoch': 3.02}
	{'loss': 0.0982, 'learning_rate': 9.224444444444445e-06, 'epoch': 3.02}
	{'loss': 0.0957, 'learning_rate': 9.168888888888889e-06, 'epoch': 3.03}
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	{'loss': 0.099, 'learning_rate': 9.057777777777779e-06, 'epoch': 3.04}
	{'loss': 0.0863, 'learning_rate': 9.002222222222223e-06, 'epoch': 3.04}

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	[INFO\|trainer.py:3142] 2023-05-10 17:47:34,809 >> Num examples: Unknown
	[INFO\|trainer.py:3143] 2023-05-10 17:47:34,809 >> Batch size = 64
	{'loss': 0.1075, 'learning_rate': 8.946666666666669e-06, 'epoch': 4.0}
	{'loss': 0.1386, 'learning_rate': 8.891111111111111e-06, 'epoch': 4.01}

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	[INFO\|trainer_utils.py:693] 2023-05-10 17:47:50,596 >> 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 [9:02:19<32:01:14, 28.82s/it][INFO\|trainer.py:2877] 2023-05-10 18:43:59,730 >> Saving model checkpoint to ./checkpoint-1000
	[INFO\|configuration_utils.py:458] 2023-05-10 18:43:59,735 >> Configuration saved in ./checkpoint-1000/config.json
	[INFO\|configuration_utils.py:364] 2023-05-10 18:43:59,739 >> Configuration saved in ./checkpoint-1000/generation_config.json
	[INFO\|modeling_utils.py:1855] 2023-05-10 18:44:03,168 >> Model weights saved in ./checkpoint-1000/pytorch_model.bin
	[INFO\|feature_extraction_utils.py:369] 2023-05-10 18:44:03,173 >> Feature extractor saved in ./checkpoint-1000/preprocessor_config.json
	[INFO\|feature_extraction_utils.py:369] 2023-05-10 18:44:11,165 >> Feature extractor saved in ./preprocessor_config.json
	Adding files tracked by Git LFS: ['wandb/run-20230509_115211-hq92t8sj/run-hq92t8sj.wandb', 'wandb/run-20230510_094132-lvsln7ks/run-lvsln7ks.wandb']. This may take a bit of time if the files are large.
	{'eval_loss': 0.24644243717193604, 'eval_wer': 9.800036380645496, 'eval_runtime': 3384.9122, 'eval_samples_per_second': 4.585, 'eval_steps_per_second': 0.072, 'epoch': 4.01}
	05/10/2023 18:44:21 - WARNING - huggingface_hub.repository - Adding files tracked by Git LFS: ['wandb/run-20230509_115211-hq92t8sj/run-hq92t8sj.wandb', 'wandb/run-20230510_094132-lvsln7ks/run-lvsln7ks.wandb']. This may take a bit of time if the files are large.