diff --git "a/log/train_log" "b/log/train_log"
new file mode 100644--- /dev/null
+++ "b/log/train_log"
@@ -0,0 +1,12239 @@
+# Running on vgni001
+# Started at Mon 28 Nov 15:12:15 CET 2022
+# python3 src/run_speech_recognition_ctc.py --report_to=none --run_name=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/ --preprocessing_num_workers=5 --model_name_or_path=facebook/wav2vec2-large-960h-lv60-self --dataset_name=experiments/data/uwb_atcc/train --min_duration_in_seconds=0.2 --max_duration_in_seconds=20 --eval_dataset_name=experiments/data/uwb_atcc/test --train_split_name=train --output_dir=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/ --num_train_epochs=50 --per_device_train_batch_size=24 --per_device_eval_batch_size=12 --gradient_accumulation_steps=1 --learning_rate=1e-4 --weight_decay=0.001 --warmup_steps=1000 --evaluation_strategy=steps --text_column_name=text --audio_column_name=audio --length_column_name=input_length '--chars_to_ignore=, ? . ! \; \: " “ % ‘ ” � — ’ … –' --save_steps=1000 --eval_steps=500 --logging_steps=1000 --layerdrop=0.0 --activation_dropout=0.0 --attention_dropout=0.0 --save_total_limit=1 --feat_proj_dropout=0.05 --mask_time_prob=0.075 --mask_time_length=12 --mask_feature_prob=0.0 --mask_feature_length=12 --gradient_checkpointing --freeze_feature_encoder --fp16 --group_by_length --do_train --do_eval --max_steps 10000 --overwrite_output_dir --freeze_feature_encoder 
+11/28/2022 15:12:25 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True
+11/28/2022 15:12:25 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
+_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=500,
+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,
+gradient_accumulation_steps=1,
+gradient_checkpointing=True,
+greater_is_better=None,
+group_by_length=True,
+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=0.0001,
+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=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/runs/Nov28_15-12-25_vgni001,
+logging_first_step=False,
+logging_nan_inf_filter=True,
+logging_steps=1000,
+logging_strategy=steps,
+lr_scheduler_type=linear,
+max_grad_norm=1.0,
+max_steps=10000,
+metric_for_best_model=None,
+mp_parameters=,
+no_cuda=False,
+num_train_epochs=50.0,
+optim=adamw_hf,
+output_dir=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/,
+overwrite_output_dir=True,
+past_index=-1,
+per_device_eval_batch_size=12,
+per_device_train_batch_size=24,
+prediction_loss_only=False,
+push_to_hub=False,
+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=[],
+resume_from_checkpoint=None,
+run_name=experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/,
+save_on_each_node=False,
+save_steps=1000,
+save_strategy=steps,
+save_total_limit=1,
+seed=42,
+sharded_ddp=[],
+skip_memory_metrics=True,
+tf32=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=1000,
+weight_decay=0.001,
+xpu_backend=None,
+)
+11/28/2022 15:12:25 - WARNING - datasets.builder - Using custom data configuration train-755c6b8b7f9b046c
+Downloading and preparing dataset atc_data_loader/train to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//train/atc_data_loader/train-755c6b8b7f9b046c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4...
+
Generating train split: 0 examples [00:00, ? examples/s]
Generating train split: 1 examples [00:25, 25.81s/ examples]
Generating train split: 256 examples [00:25, 14.05 examples/s]
Generating train split: 700 examples [00:26, 48.51 examples/s]
Generating train split: 1040 examples [00:26, 85.34 examples/s]
Generating train split: 1536 examples [00:26, 159.93 examples/s]
Generating train split: 2011 examples [00:26, 258.66 examples/s]
Generating train split: 2407 examples [00:26, 368.13 examples/s]
Generating train split: 2816 examples [00:26, 515.49 examples/s]
Generating train split: 3319 examples [00:26, 761.90 examples/s]
Generating train split: 3732 examples [00:26, 998.39 examples/s]
Generating train split: 4133 examples [00:26, 1246.55 examples/s]
Generating train split: 4608 examples [00:27, 1592.25 examples/s]
Generating train split: 5109 examples [00:27, 2059.00 examples/s]
Generating train split: 5520 examples [00:27, 2273.72 examples/s]
Generating train split: 5900 examples [00:27, 2480.44 examples/s]
Generating train split: 6400 examples [00:27, 2871.80 examples/s]
Generating train split: 6885 examples [00:27, 3299.35 examples/s]
Generating train split: 7297 examples [00:27, 3344.26 examples/s]
Generating train split: 7690 examples [00:27, 3397.37 examples/s]
Generating train split: 8192 examples [00:28, 3554.49 examples/s]
Generating train split: 8704 examples [00:28, 3660.94 examples/s]
Generating train split: 9216 examples [00:28, 3807.51 examples/s]
Generating train split: 9728 examples [00:28, 3922.50 examples/s]
Generating train split: 10238 examples [00:28, 4221.47 examples/s]
Generating train split: 10673 examples [00:28, 4114.93 examples/s]
Generating train split: 11093 examples [00:28, 3872.86 examples/s]
                                                                  
Dataset atc_data_loader downloaded and prepared to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//train/atc_data_loader/train-755c6b8b7f9b046c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4. Subsequent calls will reuse this data.
+11/28/2022 15:12:55 - WARNING - datasets.builder - Using custom data configuration test-085e5dd7a4b8bb1c
+Downloading and preparing dataset atc_data_loader/test to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//test/atc_data_loader/test-085e5dd7a4b8bb1c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4...
+
Generating test split: 0 examples [00:00, ? examples/s]
Generating test split: 1 examples [00:05,  5.73s/ examples]
Generating test split: 285 examples [00:05, 69.22 examples/s]
Generating test split: 655 examples [00:05, 191.09 examples/s]
Generating test split: 1024 examples [00:06, 348.81 examples/s]
Generating test split: 1536 examples [00:06, 634.68 examples/s]
Generating test split: 2048 examples [00:06, 979.63 examples/s]
Generating test split: 2506 examples [00:06, 1342.98 examples/s]
                                                                
loading configuration file config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/config.json
+Model config Wav2Vec2Config {
+  "_name_or_path": "facebook/wav2vec2-large-960h-lv60-self",
+  "activation_dropout": 0.1,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForCTC"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": true,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "sum",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": true,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_dropout": 0.0,
+  "feat_extract_norm": "layer",
+  "feat_proj_dropout": 0.1,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.1,
+  "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,
+  "model_type": "wav2vec2",
+  "num_adapter_layers": 3,
+  "num_attention_heads": 16,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 0,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "transformers_version": "4.24.0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 32,
+  "xvector_output_dim": 512
+}
+
+Dataset atc_data_loader downloaded and prepared to /remote/idiap.svm/temp.speech01/jzuluaga/experiments/journal/asr/github/w2v2-air-traffic/.cache/experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc//test/atc_data_loader/test-085e5dd7a4b8bb1c/0.0.0/f2633cc53c6abe32cddd4152eebde1a4e3c9953e1446e190b8d9a13330cddaa4. Subsequent calls will reuse this data.
+
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+
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+loading file vocab.json
+loading file tokenizer_config.json
+loading file added_tokens.json
+loading file special_tokens_map.json
+Adding <s> to the vocabulary
+Adding </s> to the vocabulary
+Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
+loading configuration file preprocessor_config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/preprocessor_config.json
+loading configuration file config.json from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/config.json
+Model config Wav2Vec2Config {
+  "_name_or_path": "facebook/wav2vec2-large-960h-lv60-self",
+  "activation_dropout": 0.1,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForCTC"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": true,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "sum",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": true,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_dropout": 0.0,
+  "feat_extract_norm": "layer",
+  "feat_proj_dropout": 0.1,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.1,
+  "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,
+  "model_type": "wav2vec2",
+  "num_adapter_layers": 3,
+  "num_attention_heads": 16,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 0,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "transformers_version": "4.24.0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 32,
+  "xvector_output_dim": 512
+}
+
+Feature extractor Wav2Vec2FeatureExtractor {
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}
+
+loading weights file pytorch_model.bin from cache at /idiap/temp/jzuluaga/cache/huggingface/models--facebook--wav2vec2-large-960h-lv60-self/snapshots/54074b1c16f4de6a5ad59affb4caa8f2ea03a119/pytorch_model.bin
+All model checkpoint weights were used when initializing Wav2Vec2ForCTC.
+
+Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-large-960h-lv60-self and are newly initialized: ['wav2vec2.masked_spec_embed']
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-large-960h-lv60-self and are newly initialized because the shapes did not match:
+- lm_head.weight: found shape torch.Size([32, 1024]) in the checkpoint and torch.Size([31, 1024]) in the model instantiated
+- lm_head.bias: found shape torch.Size([32]) in the checkpoint and torch.Size([31]) in the model instantiated
+You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
+
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+
+
+
preprocess datasets #4:   0%|          | 0/2258 [00:00<?, ?ex/s]/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
+
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
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preprocess datasets #0:  14%|█▍        | 326/2259 [00:13<01:04, 29.74ex/s]
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preprocess datasets #0:  15%|█▍        | 331/2259 [00:13<00:55, 34.52ex/s]
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preprocess datasets #0:  15%|█▌        | 344/2259 [00:13<00:56, 33.91ex/s]
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preprocess datasets #0:  17%|█▋        | 377/2259 [00:14<00:43, 43.60ex/s]
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preprocess datasets #0:  17%|█▋        | 391/2259 [00:15<00:51, 36.57ex/s]
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preprocess datasets #3:  84%|████████▍ | 1893/2258 [01:01<00:12, 29.58ex/s]
+
preprocess datasets #1:  79%|███████▉  | 1794/2258 [01:01<00:11, 40.51ex/s]
preprocess datasets #0:  81%|████████  | 1834/2259 [01:01<00:10, 41.08ex/s]
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preprocess datasets #4:  86%|████████▌ | 1933/2258 [01:01<00:10, 31.29ex/s]
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preprocess datasets #2:  82%|████████▏ | 1858/2258 [01:01<00:12, 33.06ex/s]
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preprocess datasets #1:  80%|███████▉  | 1799/2258 [01:01<00:10, 42.27ex/s]
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preprocess datasets #3:  84%|████████▍ | 1897/2258 [01:01<00:11, 31.09ex/s]
preprocess datasets #0:  81%|████████▏ | 1839/2259 [01:01<00:10, 39.94ex/s]
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preprocess datasets #2:  82%|████████▏ | 1862/2258 [01:01<00:11, 34.56ex/s]
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preprocess datasets #4:  86%|████████▌ | 1937/2258 [01:01<00:10, 29.42ex/s]
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preprocess datasets #1:  80%|███████▉  | 1805/2258 [01:01<00:10, 43.88ex/s]
+
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preprocess datasets #3:  84%|████████▍ | 1902/2258 [01:01<00:11, 30.85ex/s]
preprocess datasets #0:  82%|████████▏ | 1844/2259 [01:01<00:10, 39.92ex/s]
+
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preprocess datasets #4:  86%|████████▌ | 1941/2258 [01:01<00:10, 31.56ex/s]
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preprocess datasets #2:  83%|████████▎ | 1867/2258 [01:01<00:10, 35.91ex/s]
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preprocess datasets #3:  84%|████████▍ | 1907/2258 [01:01<00:10, 34.61ex/s]
+
preprocess datasets #1:  80%|████████  | 1811/2258 [01:01<00:10, 42.17ex/s]
+
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preprocess datasets #2:  83%|████████▎ | 1871/2258 [01:02<00:10, 36.32ex/s]
preprocess datasets #0:  82%|████████▏ | 1849/2259 [01:02<00:10, 39.82ex/s]
+
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preprocess datasets #4:  86%|████████▌ | 1945/2258 [01:02<00:10, 30.62ex/s]
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preprocess datasets #3:  85%|████████▍ | 1911/2258 [01:02<00:09, 35.90ex/s]
+
preprocess datasets #1:  80%|████████  | 1816/2258 [01:02<00:10, 43.28ex/s]
+
+
preprocess datasets #2:  83%|████████▎ | 1875/2258 [01:02<00:10, 36.99ex/s]
preprocess datasets #0:  82%|████████▏ | 1856/2259 [01:02<00:08, 45.27ex/s]
+
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preprocess datasets #4:  86%|████████▋ | 1951/2258 [01:02<00:08, 34.62ex/s]
+
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preprocess datasets #3:  85%|████████▍ | 1916/2258 [01:02<00:09, 36.69ex/s]
+
preprocess datasets #1:  81%|████████  | 1823/2258 [01:02<00:09, 46.53ex/s]
+
+
preprocess datasets #2:  83%|████████▎ | 1881/2258 [01:02<00:09, 39.88ex/s]
preprocess datasets #0:  82%|████████▏ | 1861/2259 [01:02<00:09, 43.49ex/s]
+
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preprocess datasets #4:  87%|████████▋ | 1955/2258 [01:02<00:09, 32.83ex/s]
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preprocess datasets #3:  85%|████████▌ | 1921/2258 [01:02<00:09, 37.14ex/s]
+
preprocess datasets #1:  81%|████████  | 1828/2258 [01:02<00:09, 43.32ex/s]
+
+
preprocess datasets #2:  83%|████████▎ | 1885/2258 [01:02<00:09, 39.89ex/s]
preprocess datasets #0:  83%|████████▎ | 1867/2259 [01:02<00:08, 46.55ex/s]
+
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preprocess datasets #3:  85%|████████▌ | 1925/2258 [01:02<00:09, 36.83ex/s]
+
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preprocess datasets #4:  87%|████████▋ | 1959/2258 [01:02<00:09, 31.60ex/s]
+
preprocess datasets #1:  81%|████████  | 1833/2258 [01:02<00:09, 43.24ex/s]
+
+
preprocess datasets #2:  84%|████████▎ | 1890/2258 [01:02<00:08, 42.10ex/s]
preprocess datasets #0:  83%|████████▎ | 1872/2259 [01:02<00:08, 46.05ex/s]
+
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+
preprocess datasets #3:  85%|████████▌ | 1929/2258 [01:02<00:09, 34.49ex/s]
+
preprocess datasets #1:  81%|████████▏ | 1838/2258 [01:02<00:09, 42.40ex/s]
+
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+
preprocess datasets #4:  87%|████████▋ | 1963/2258 [01:02<00:09, 30.96ex/s]
+
+
preprocess datasets #2:  84%|████████▍ | 1895/2258 [01:02<00:09, 36.59ex/s]
preprocess datasets #0:  83%|████████▎ | 1877/2259 [01:02<00:09, 40.77ex/s]
+
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preprocess datasets #3:  86%|████████▌ | 1933/2258 [01:02<00:09, 35.26ex/s]
+
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+
preprocess datasets #4:  87%|████████▋ | 1967/2258 [01:02<00:09, 30.44ex/s]
+
preprocess datasets #1:  82%|████████▏ | 1843/2258 [01:02<00:10, 37.96ex/s]
+
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preprocess datasets #2:  84%|████████▍ | 1899/2258 [01:02<00:10, 34.51ex/s]
+
+
+
preprocess datasets #3:  86%|████████▌ | 1937/2258 [01:02<00:08, 35.87ex/s]
preprocess datasets #0:  83%|████████▎ | 1882/2259 [01:02<00:09, 38.07ex/s]
+
preprocess datasets #1:  82%|████████▏ | 1847/2258 [01:02<00:11, 36.47ex/s]
+
+
+
+
preprocess datasets #4:  87%|████████▋ | 1971/2258 [01:02<00:09, 29.61ex/s]
+
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preprocess datasets #2:  84%|████████▍ | 1903/2258 [01:02<00:10, 34.54ex/s]
+
+
+
preprocess datasets #3:  86%|████████▌ | 1942/2258 [01:02<00:08, 39.03ex/s]
preprocess datasets #0:  83%|████████▎ | 1886/2259 [01:02<00:09, 37.51ex/s]
+
+
+
+
preprocess datasets #4:  87%|████████▋ | 1974/2258 [01:02<00:09, 28.90ex/s]
+
preprocess datasets #1:  82%|████████▏ | 1851/2258 [01:03<00:11, 35.08ex/s]
+
+
+
preprocess datasets #3:  86%|████████▌ | 1946/2258 [01:03<00:08, 38.12ex/s]
+
+
preprocess datasets #2:  84%|████████▍ | 1907/2258 [01:03<00:10, 34.40ex/s]
preprocess datasets #0:  84%|████████▎ | 1891/2259 [01:03<00:09, 39.96ex/s]
+
+
+
+
preprocess datasets #4:  88%|████████▊ | 1979/2258 [01:03<00:08, 32.88ex/s]
+
preprocess datasets #1:  82%|████████▏ | 1855/2258 [01:03<00:11, 35.14ex/s]
+
+
preprocess datasets #2:  85%|████████▍ | 1911/2258 [01:03<00:10, 33.16ex/s]
+
+
+
preprocess datasets #3:  86%|████████▋ | 1950/2258 [01:03<00:08, 34.39ex/s]
preprocess datasets #0:  84%|████████▍ | 1896/2259 [01:03<00:09, 39.59ex/s]
+
+
+
+
preprocess datasets #4:  88%|████████▊ | 1983/2258 [01:03<00:08, 33.59ex/s]
+
preprocess datasets #1:  82%|████████▏ | 1859/2258 [01:03<00:11, 35.96ex/s]
+
+
preprocess datasets #2:  85%|████████▍ | 1915/2258 [01:03<00:10, 34.18ex/s]
preprocess datasets #0:  84%|████████▍ | 1901/2259 [01:03<00:09, 35.84ex/s]
+
+
+
+
preprocess datasets #4:  88%|████████▊ | 1987/2258 [01:03<00:07, 33.95ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1954/2258 [01:03<00:10, 28.89ex/s]
+
+
preprocess datasets #2:  85%|████████▍ | 1919/2258 [01:03<00:10, 33.49ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1863/2258 [01:03<00:12, 30.71ex/s]
+
+
+
+
preprocess datasets #4:  88%|████████▊ | 1992/2258 [01:03<00:07, 36.44ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1959/2258 [01:03<00:09, 31.10ex/s]
preprocess datasets #0:  84%|████████▍ | 1905/2259 [01:03<00:10, 32.30ex/s]
+
+
preprocess datasets #2:  85%|████████▌ | 1923/2258 [01:03<00:09, 33.77ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1867/2258 [01:03<00:12, 32.25ex/s]
+
+
+
+
preprocess datasets #4:  88%|████████▊ | 1997/2258 [01:03<00:07, 37.03ex/s]
preprocess datasets #0:  85%|████████▍ | 1909/2259 [01:03<00:10, 33.19ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1871/2258 [01:03<00:11, 32.99ex/s]
+
+
preprocess datasets #2:  85%|████████▌ | 1927/2258 [01:03<00:10, 31.93ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1963/2258 [01:03<00:10, 27.79ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1875/2258 [01:03<00:11, 33.52ex/s]
+
+
preprocess datasets #2:  86%|████████▌ | 1931/2258 [01:03<00:10, 32.34ex/s]
preprocess datasets #0:  85%|████████▍ | 1913/2259 [01:03<00:11, 30.63ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1967/2258 [01:03<00:10, 28.46ex/s]
preprocess datasets #0:  85%|████████▍ | 1917/2259 [01:03<00:10, 31.42ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1879/2258 [01:03<00:12, 30.89ex/s]
+
+
preprocess datasets #2:  86%|████████▌ | 1935/2258 [01:03<00:11, 29.20ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1971/2258 [01:03<00:10, 28.42ex/s]
preprocess datasets #0:  85%|████████▌ | 1921/2259 [01:04<00:10, 33.25ex/s]
+
+
preprocess datasets #2:  86%|████████▌ | 1939/2258 [01:04<00:10, 31.47ex/s]
+
preprocess datasets #1:  83%|████████▎ | 1883/2258 [01:04<00:12, 29.05ex/s]
+
+
+
preprocess datasets #3:  87%|████████▋ | 1974/2258 [01:04<00:10, 26.84ex/s]
preprocess datasets #0:  85%|████████▌ | 1925/2259 [01:04<00:09, 33.56ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▊ | 2001/2258 [01:04<00:15, 16.76ex/s]
+
+
+
preprocess datasets #3:  88%|████████▊ | 1977/2258 [01:04<00:10, 27.51ex/s]
+
preprocess datasets #1:  84%|████████▎ | 1886/2258 [01:04<00:14, 25.43ex/s]
+
+
preprocess datasets #2:  86%|████████▌ | 1943/2258 [01:04<00:11, 27.41ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▉ | 2004/2258 [01:04<00:13, 18.50ex/s]
+
+
+
preprocess datasets #3:  88%|████████▊ | 1982/2258 [01:04<00:08, 32.36ex/s]
preprocess datasets #0:  85%|████████▌ | 1929/2259 [01:04<00:11, 27.72ex/s]
+
+
preprocess datasets #2:  86%|████████▌ | 1946/2258 [01:04<00:11, 27.60ex/s]
+
preprocess datasets #1:  84%|████████▎ | 1889/2258 [01:04<00:14, 25.84ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▉ | 2007/2258 [01:04<00:12, 20.19ex/s]
+
+
+
preprocess datasets #3:  88%|████████▊ | 1987/2258 [01:04<00:07, 35.46ex/s]
preprocess datasets #0:  86%|████████▌ | 1933/2259 [01:04<00:10, 30.44ex/s]
+
preprocess datasets #1:  84%|████████▍ | 1892/2258 [01:04<00:14, 25.38ex/s]
+
+
preprocess datasets #2:  86%|████████▋ | 1949/2258 [01:04<00:12, 24.19ex/s]
preprocess datasets #0:  86%|████████▌ | 1939/2259 [01:04<00:08, 37.25ex/s]
+
+
+
preprocess datasets #3:  88%|████████▊ | 1992/2258 [01:04<00:06, 38.44ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▉ | 2011/2258 [01:04<00:10, 22.61ex/s]
+
preprocess datasets #1:  84%|████████▍ | 1896/2258 [01:04<00:14, 25.79ex/s]
+
+
preprocess datasets #2:  86%|████████▋ | 1953/2258 [01:04<00:11, 26.88ex/s]
+
+
+
preprocess datasets #3:  88%|████████▊ | 1998/2258 [01:04<00:06, 41.18ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▉ | 2014/2258 [01:04<00:10, 23.00ex/s]
preprocess datasets #0:  86%|████████▌ | 1944/2259 [01:04<00:09, 34.24ex/s]
+
preprocess datasets #1:  84%|████████▍ | 1900/2258 [01:04<00:13, 27.00ex/s]
+
+
+
+
preprocess datasets #4:  89%|████████▉ | 2017/2258 [01:04<00:09, 24.46ex/s]
+
+
preprocess datasets #2:  87%|████████▋ | 1959/2258 [01:04<00:09, 31.13ex/s]
preprocess datasets #0:  86%|████████▌ | 1948/2259 [01:04<00:10, 30.71ex/s]
+
+
+
+
preprocess datasets #4:  90%|████████▉ | 2021/2258 [01:04<00:09, 25.66ex/s]
+
preprocess datasets #1:  84%|████████▍ | 1903/2258 [01:04<00:15, 22.25ex/s]
+
+
preprocess datasets #2:  87%|████████▋ | 1963/2258 [01:04<00:10, 27.75ex/s]
+
+
+
+
preprocess datasets #4:  90%|████████▉ | 2026/2258 [01:04<00:07, 30.40ex/s]
preprocess datasets #0:  86%|████████▋ | 1952/2259 [01:05<00:10, 28.41ex/s]
+
+
preprocess datasets #2:  87%|████████▋ | 1967/2258 [01:05<00:09, 30.01ex/s]
+
preprocess datasets #1:  84%|████████▍ | 1908/2258 [01:05<00:12, 27.57ex/s]
+
+
+
+
preprocess datasets #4:  90%|████████▉ | 2030/2258 [01:05<00:07, 32.55ex/s]
preprocess datasets #0:  87%|████████▋ | 1956/2259 [01:05<00:10, 29.48ex/s]
+
+
preprocess datasets #2:  87%|████████▋ | 1972/2258 [01:05<00:08, 33.30ex/s]
+
preprocess datasets #1:  85%|████████▍ | 1912/2258 [01:05<00:12, 28.37ex/s]
+
+
+
preprocess datasets #3:  89%|████████▊ | 2003/2258 [01:05<00:13, 19.52ex/s]
+
+
+
+
preprocess datasets #4:  90%|█████████ | 2036/2258 [01:05<00:05, 37.49ex/s]
+
+
preprocess datasets #2:  88%|████████▊ | 1976/2258 [01:05<00:08, 33.86ex/s]
preprocess datasets #0:  87%|████████▋ | 1960/2259 [01:05<00:10, 27.73ex/s]
+
+
+
+
preprocess datasets #4:  90%|█████████ | 2042/2258 [01:05<00:05, 42.53ex/s]
+
preprocess datasets #1:  85%|████████▍ | 1916/2258 [01:05<00:12, 27.69ex/s]
+
+
preprocess datasets #2:  88%|████████▊ | 1980/2258 [01:05<00:08, 34.42ex/s]
+
+
+
preprocess datasets #3:  89%|████████▉ | 2007/2258 [01:05<00:13, 19.09ex/s]
+
+
+
+
preprocess datasets #4:  91%|█████████ | 2047/2258 [01:05<00:04, 43.55ex/s]
preprocess datasets #0:  87%|████████▋ | 1963/2259 [01:05<00:11, 25.35ex/s]
+
preprocess datasets #1:  85%|████████▍ | 1919/2258 [01:05<00:13, 26.07ex/s]
+
+
preprocess datasets #2:  88%|████████▊ | 1985/2258 [01:05<00:07, 38.25ex/s]
+
+
+
+
preprocess datasets #4:  91%|█████████ | 2052/2258 [01:05<00:04, 42.45ex/s]
preprocess datasets #0:  87%|████████▋ | 1967/2259 [01:05<00:10, 27.22ex/s]
+
+
+
preprocess datasets #3:  89%|████████▉ | 2010/2258 [01:05<00:12, 19.18ex/s]
+
+
preprocess datasets #2:  88%|████████▊ | 1990/2258 [01:05<00:06, 39.65ex/s]
+
preprocess datasets #1:  85%|████████▌ | 1923/2258 [01:05<00:12, 26.76ex/s]
preprocess datasets #0:  87%|████████▋ | 1972/2259 [01:05<00:08, 32.48ex/s]
+
+
+
+
preprocess datasets #4:  91%|█████████ | 2057/2258 [01:05<00:04, 42.10ex/s]
+
+
+
preprocess datasets #3:  89%|████████▉ | 2013/2258 [01:05<00:11, 20.62ex/s]
+
preprocess datasets #1:  85%|████████▌ | 1926/2258 [01:05<00:12, 26.57ex/s]
+
+
preprocess datasets #2:  88%|████████▊ | 1995/2258 [01:05<00:07, 35.69ex/s]
+
+
+
+
preprocess datasets #4:  91%|█████████▏| 2062/2258 [01:05<00:04, 41.78ex/s]
preprocess datasets #0:  87%|████████▋ | 1976/2259 [01:05<00:09, 29.38ex/s]
+
preprocess datasets #1:  85%|████████▌ | 1929/2258 [01:05<00:13, 25.28ex/s]
+
+
+
preprocess datasets #3:  89%|████████▉ | 2016/2258 [01:05<00:12, 19.64ex/s]
+
+
+
+
preprocess datasets #4:  92%|█████████▏| 2067/2258 [01:05<00:04, 38.22ex/s]
+
preprocess datasets #1:  86%|████████▌ | 1932/2258 [01:06<00:13, 24.73ex/s]
+
+
+
preprocess datasets #3:  89%|████████▉ | 2020/2258 [01:05<00:10, 22.16ex/s]
preprocess datasets #0:  88%|████████▊ | 1980/2259 [01:06<00:10, 25.85ex/s]
+
+
+
+
preprocess datasets #4:  92%|█████████▏| 2071/2258 [01:06<00:05, 37.25ex/s]
+
+
+
preprocess datasets #3:  90%|████████▉ | 2023/2258 [01:06<00:10, 23.38ex/s]
+
preprocess datasets #1:  86%|████████▌ | 1937/2258 [01:06<00:11, 28.12ex/s]
preprocess datasets #0:  88%|████████▊ | 1983/2259 [01:06<00:11, 24.50ex/s]
+
+
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+
preprocess datasets #4:  92%|█████████▏| 2077/2258 [01:06<00:04, 41.37ex/s]
+
+
+
preprocess datasets #3:  90%|████████▉ | 2028/2258 [01:06<00:07, 29.20ex/s]
+
preprocess datasets #1:  86%|████████▌ | 1940/2258 [01:06<00:12, 25.07ex/s]
preprocess datasets #0:  88%|████████▊ | 1987/2259 [01:06<00:10, 27.17ex/s]
+
+
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preprocess datasets #4:  92%|█████████▏| 2082/2258 [01:06<00:04, 42.30ex/s]
+
+
+
preprocess datasets #3:  90%|████████▉ | 2032/2258 [01:06<00:07, 30.16ex/s]
+
preprocess datasets #1:  86%|████████▌ | 1943/2258 [01:06<00:12, 25.99ex/s]
preprocess datasets #0:  88%|████████▊ | 1990/2259 [01:06<00:09, 27.52ex/s]
+
+
preprocess datasets #2:  89%|████████▊ | 2000/2258 [01:06<00:15, 16.59ex/s]
+
+
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+
preprocess datasets #4:  92%|█████████▏| 2087/2258 [01:06<00:04, 37.97ex/s]
+
+
+
preprocess datasets #3:  90%|█████████ | 2036/2258 [01:06<00:07, 29.00ex/s]
+
preprocess datasets #1:  86%|████████▌ | 1946/2258 [01:06<00:13, 22.89ex/s]
+
+
+
+
preprocess datasets #4:  93%|█████████▎| 2092/2258 [01:06<00:04, 40.62ex/s]
+
+
preprocess datasets #2:  89%|████████▉ | 2004/2258 [01:06<00:13, 18.77ex/s]
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preprocess datasets #0:  88%|████████▊ | 1993/2259 [01:06<00:11, 23.51ex/s]
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preprocess datasets #0:  88%|████████▊ | 1996/2259 [01:06<00:10, 24.15ex/s]
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preprocess datasets #0:  88%|████████▊ | 1999/2259 [01:06<00:11, 23.63ex/s]
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preprocess datasets #1:  86%|████████▋ | 1952/2258 [01:06<00:13, 22.10ex/s]
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preprocess datasets #2:  89%|████████▉ | 2016/2258 [01:07<00:10, 22.09ex/s]
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preprocess datasets #1:  87%|████████▋ | 1962/2258 [01:07<00:09, 30.96ex/s]
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preprocess datasets #2:  89%|████████▉ | 2020/2258 [01:07<00:10, 23.15ex/s]
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preprocess datasets #1:  87%|████████▋ | 1966/2258 [01:07<00:09, 29.33ex/s]
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preprocess datasets #0:  89%|████████▊ | 2002/2259 [01:07<00:23, 11.00ex/s]
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preprocess datasets #2:  90%|████████▉ | 2031/2258 [01:07<00:08, 25.52ex/s]
preprocess datasets #0:  89%|████████▉ | 2005/2259 [01:07<00:19, 13.10ex/s]
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preprocess datasets #1:  88%|████████▊ | 1978/2258 [01:07<00:11, 25.07ex/s]
preprocess datasets #0:  89%|████████▉ | 2008/2259 [01:07<00:17, 14.67ex/s]
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preprocess datasets #1:  88%|████████▊ | 1981/2258 [01:07<00:11, 24.73ex/s]
preprocess datasets #0:  89%|████████▉ | 2011/2259 [01:07<00:15, 15.95ex/s]
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preprocess datasets #1:  88%|████████▊ | 1985/2258 [01:08<00:10, 26.42ex/s]
preprocess datasets #0:  89%|████████▉ | 2015/2259 [01:08<00:12, 19.63ex/s]
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preprocess datasets #4:  95%|█████████▍| 2143/2258 [01:08<00:03, 35.07ex/s]
preprocess datasets #0:  89%|████████▉ | 2020/2259 [01:08<00:09, 25.69ex/s]
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preprocess datasets #1:  88%|████████▊ | 1989/2258 [01:08<00:09, 27.59ex/s]
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preprocess datasets #1:  88%|████████▊ | 1993/2258 [01:08<00:09, 28.69ex/s]
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preprocess datasets #3:  92%|█████████▏| 2088/2258 [01:08<00:06, 25.05ex/s]
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preprocess datasets #1:  88%|████████▊ | 1996/2258 [01:08<00:09, 28.63ex/s]
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preprocess datasets #2:  91%|█████████ | 2049/2258 [01:08<00:09, 21.46ex/s]
preprocess datasets #0:  90%|████████▉ | 2024/2259 [01:08<00:11, 21.10ex/s]
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preprocess datasets #3:  93%|█████████▎| 2094/2258 [01:08<00:05, 30.61ex/s]
preprocess datasets #0:  90%|████████▉ | 2027/2259 [01:08<00:10, 22.66ex/s]
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preprocess datasets #4:  95%|█████████▌| 2156/2258 [01:08<00:03, 30.73ex/s]
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preprocess datasets #2:  91%|█████████ | 2057/2258 [01:08<00:07, 27.27ex/s]
preprocess datasets #0:  90%|████████▉ | 2030/2259 [01:08<00:09, 23.29ex/s]
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preprocess datasets #2:  91%|█████████▏| 2061/2258 [01:08<00:06, 28.79ex/s]
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preprocess datasets #3:  93%|█████████▎| 2102/2258 [01:08<00:04, 31.58ex/s]
preprocess datasets #0:  90%|█████████ | 2035/2259 [01:08<00:08, 27.47ex/s]
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preprocess datasets #0:  90%|█████████ | 2040/2259 [01:08<00:07, 30.89ex/s]
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preprocess datasets #2:  91%|█████████▏| 2064/2258 [01:08<00:07, 24.76ex/s]
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preprocess datasets #4:  96%|█████████▌| 2167/2258 [01:08<00:03, 26.82ex/s]
preprocess datasets #0:  90%|█████████ | 2044/2259 [01:09<00:07, 29.71ex/s]
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preprocess datasets #3:  93%|█████████▎| 2110/2258 [01:09<00:05, 27.67ex/s]
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preprocess datasets #4:  96%|█████████▌| 2170/2258 [01:09<00:03, 25.03ex/s]
preprocess datasets #0:  91%|█████████ | 2049/2259 [01:09<00:06, 32.55ex/s]
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preprocess datasets #2:  92%|█████████▏| 2073/2258 [01:09<00:06, 29.91ex/s]
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preprocess datasets #3:  94%|█████████▎| 2113/2258 [01:09<00:05, 25.46ex/s]
preprocess datasets #0:  91%|█████████ | 2053/2259 [01:09<00:06, 30.54ex/s]
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preprocess datasets #2:  92%|█████████▏| 2077/2258 [01:09<00:06, 28.40ex/s]
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preprocess datasets #3:  94%|█████████▎| 2116/2258 [01:09<00:05, 24.86ex/s]
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preprocess datasets #4:  97%|█████████▋| 2184/2258 [01:09<00:01, 38.20ex/s]
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preprocess datasets #2:  92%|█████████▏| 2081/2258 [01:09<00:05, 29.95ex/s]
preprocess datasets #0:  91%|█████████ | 2057/2259 [01:09<00:06, 29.93ex/s]
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preprocess datasets #3:  94%|█████████▍| 2119/2258 [01:09<00:05, 25.69ex/s]
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preprocess datasets #1:  89%|████████▊ | 2000/2258 [01:09<00:28,  9.08ex/s]
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preprocess datasets #4:  97%|█████████▋| 2190/2258 [01:09<00:01, 42.79ex/s]
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preprocess datasets #1:  89%|████████▉ | 2004/2258 [01:09<00:21, 11.94ex/s]
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preprocess datasets #2:  92%|█████████▏| 2085/2258 [01:09<00:05, 30.41ex/s]
preprocess datasets #0:  91%|█████████ | 2061/2259 [01:09<00:06, 30.05ex/s]
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preprocess datasets #4:  97%|█████████▋| 2196/2258 [01:09<00:01, 44.54ex/s]
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preprocess datasets #1:  89%|████████▉ | 2007/2258 [01:09<00:18, 13.85ex/s]
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preprocess datasets #2:  93%|█████████▎| 2089/2258 [01:09<00:05, 30.53ex/s]
preprocess datasets #0:  91%|█████████▏| 2065/2259 [01:09<00:06, 28.91ex/s]
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preprocess datasets #1:  89%|████████▉ | 2010/2258 [01:09<00:15, 15.50ex/s]
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preprocess datasets #1:  89%|████████▉ | 2013/2258 [01:09<00:14, 17.18ex/s]
preprocess datasets #0:  92%|█████████▏| 2074/2259 [01:09<00:05, 31.81ex/s]
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preprocess datasets #1:  89%|████████▉ | 2019/2258 [01:10<00:11, 20.65ex/s]
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preprocess datasets #0:  92%|█████████▏| 2078/2259 [01:10<00:06, 27.62ex/s]
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preprocess datasets #0:  92%|█████████▏| 2082/2259 [01:10<00:06, 27.72ex/s]
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preprocess datasets #4:   0%|          | 0/564 [00:00<?, ?ex/s]/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/lib/python3.10/site-packages/datasets/features/audio.py:279: FutureWarning: Pass orig_sr=8000, target_sr=16000 as keyword args. From version 0.10 passing these as positional arguments will result in an error
+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
+
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+  array = librosa.resample(array, sampling_rate, self.sampling_rate, res_type="kaiser_best")
+
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preprocess datasets #1:   2%|▏         | 9/565 [00:01<01:12,  7.63ex/s]
preprocess datasets #0:   2%|▏         | 12/565 [00:01<00:49, 11.07ex/s]
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preprocess datasets #3:   2%|▏         | 12/564 [00:01<00:48, 11.32ex/s]
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preprocess datasets #2:   3%|▎         | 15/564 [00:01<00:37, 14.64ex/s]
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preprocess datasets #4:   2%|▏         | 12/564 [00:01<00:50, 10.90ex/s]
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preprocess datasets #1:   2%|▏         | 13/565 [00:01<00:49, 11.19ex/s]
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preprocess datasets #3:   3%|▎         | 15/564 [00:01<00:38, 14.19ex/s]
preprocess datasets #0:   3%|▎         | 18/565 [00:01<00:30, 17.66ex/s]
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preprocess datasets #2:   3%|▎         | 19/564 [00:01<00:31, 17.42ex/s]
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preprocess datasets #1:   3%|▎         | 16/565 [00:02<00:41, 13.36ex/s]
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preprocess datasets #3:   3%|▎         | 18/564 [00:01<00:33, 16.35ex/s]
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preprocess datasets #2:   4%|▍         | 23/564 [00:02<00:26, 20.41ex/s]
preprocess datasets #0:   4%|▍         | 22/565 [00:02<00:28, 18.86ex/s]
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preprocess datasets #2:   5%|▍         | 28/564 [00:02<00:21, 24.85ex/s]
preprocess datasets #0:   5%|▍         | 26/565 [00:02<00:24, 21.92ex/s]
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preprocess datasets #4:   4%|▎         | 21/564 [00:02<00:34, 15.67ex/s]
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preprocess datasets #2:   6%|▌         | 32/564 [00:02<00:20, 26.35ex/s]
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preprocess datasets #1:   4%|▍         | 22/565 [00:02<00:35, 15.09ex/s]
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preprocess datasets #3:   5%|▌         | 29/564 [00:02<00:21, 24.87ex/s]
preprocess datasets #0:   5%|▌         | 30/565 [00:02<00:23, 22.40ex/s]
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preprocess datasets #0:   6%|▌         | 34/565 [00:02<00:21, 24.39ex/s]
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preprocess datasets #0:   7%|▋         | 37/565 [00:02<00:24, 21.98ex/s]
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preprocess datasets #0:   7%|▋         | 41/565 [00:02<00:20, 25.04ex/s]
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preprocess datasets #0:   8%|▊         | 45/565 [00:02<00:19, 26.46ex/s]
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preprocess datasets #0:   9%|▉         | 50/565 [00:03<00:18, 28.54ex/s]
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preprocess datasets #0:  10%|▉         | 54/565 [00:03<00:17, 28.87ex/s]
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preprocess datasets #2:  10%|█         | 58/564 [00:03<00:17, 29.11ex/s]
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preprocess datasets #0:  10%|█         | 58/565 [00:03<00:16, 31.14ex/s]
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preprocess datasets #0:  11%|█         | 62/565 [00:03<00:16, 30.13ex/s]
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preprocess datasets #0:  12%|█▏        | 66/565 [00:03<00:16, 30.95ex/s]
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preprocess datasets #0:  12%|█▏        | 70/565 [00:03<00:15, 32.85ex/s]
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preprocess datasets #0:  13%|█▎        | 75/565 [00:03<00:13, 35.80ex/s]
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preprocess datasets #0:  14%|█▍        | 79/565 [00:03<00:15, 31.99ex/s]
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preprocess datasets #0:  15%|█▍        | 83/565 [00:04<00:15, 30.85ex/s]
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preprocess datasets #0:  16%|█▌        | 89/565 [00:04<00:13, 35.38ex/s]
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preprocess datasets #0:  16%|█▋        | 93/565 [00:04<00:13, 34.37ex/s]
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preprocess datasets #0:  17%|█▋        | 97/565 [00:04<00:13, 34.54ex/s]
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preprocess datasets #0:  18%|█▊        | 101/565 [00:04<00:13, 34.14ex/s]
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preprocess datasets #0:  19%|█▉        | 107/565 [00:04<00:11, 39.76ex/s]
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preprocess datasets #0:  21%|██        | 116/565 [00:05<00:13, 33.41ex/s]
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preprocess datasets #0:  21%|██▏       | 121/565 [00:05<00:13, 33.97ex/s]
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+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+tokenizer config file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/tokenizer_config.json
+Special tokens file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/special_tokens_map.json
+added tokens file saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/added_tokens.json
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+Model config Wav2Vec2Config {
+  "_name_or_path": "experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/",
+  "activation_dropout": 0.0,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForCTC"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": true,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "mean",
+  "ctc_zero_infinity": true,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": true,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_dropout": 0.0,
+  "feat_extract_norm": "layer",
+  "feat_proj_dropout": 0.05,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.0,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.0,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.0,
+  "mask_feature_length": 12,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 12,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.075,
+  "model_type": "wav2vec2",
+  "num_adapter_layers": 3,
+  "num_attention_heads": 16,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 28,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "transformers_version": "4.24.0",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 31,
+  "xvector_output_dim": 512
+}
+
+loading configuration file experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+Feature extractor Wav2Vec2FeatureExtractor {
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}
+
+loading file vocab.json
+loading file tokenizer_config.json
+loading file added_tokens.json
+loading file special_tokens_map.json
+Adding <s> to the vocabulary
+Adding </s> to the vocabulary
+max_steps is given, it will override any value given in num_train_epochs
+Using cuda_amp half precision backend
+The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+/idiap/user/jzuluaga/miniconda3/envs/w2v2/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(
+***** Running training *****
+  Num examples = 11291
+  Num Epochs = 22
+  Instantaneous batch size per device = 24
+  Total train batch size (w. parallel, distributed & accumulation) = 24
+  Gradient Accumulation steps = 1
+  Total optimization steps = 10000
+  Number of trainable parameters = 311260319
+
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  5%|▌         | 500/10000 [07:31<2:07:58,  1.24it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+
+
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 10%|█         | 1000/10000 [16:14<3:35:28,  1.44s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 2.901623249053955, 'eval_wer': 0.9995142002989537, 'eval_runtime': 78.4215, 'eval_samples_per_second': 35.985, 'eval_steps_per_second': 3.009, 'epoch': 1.06}
+{'loss': 2.877, 'learning_rate': 9.970000000000001e-05, 'epoch': 2.12}
+
+
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+
                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000/preprocessor_config.json
+
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.981178343296051, 'eval_wer': 0.3484678624813154, 'eval_runtime': 78.2116, 'eval_samples_per_second': 36.082, 'eval_steps_per_second': 3.017, 'epoch': 2.12}
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 20%|██        | 2000/10000 [33:42<2:25:44,  1.09s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.784228503704071, 'eval_wer': 0.273168908819133, 'eval_runtime': 78.8199, 'eval_samples_per_second': 35.803, 'eval_steps_per_second': 2.994, 'epoch': 3.18}
+{'loss': 0.7834, 'learning_rate': 8.892222222222223e-05, 'epoch': 4.25}
+
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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-1000] due to args.save_total_limit
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6962451934814453, 'eval_wer': 0.21917040358744394, 'eval_runtime': 78.959, 'eval_samples_per_second': 35.74, 'eval_steps_per_second': 2.989, 'epoch': 4.25}
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 30%|███       | 3000/10000 [51:11<1:43:26,  1.13it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6526582837104797, 'eval_wer': 0.20418535127055307, 'eval_runtime': 78.1018, 'eval_samples_per_second': 36.132, 'eval_steps_per_second': 3.022, 'epoch': 5.31}
+{'loss': 0.6084, 'learning_rate': 7.78111111111111e-05, 'epoch': 6.37}
+
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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-2000] due to args.save_total_limit
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 35%|███▌      | 3500/10000 [59:50<2:13:30,  1.23s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6220057606697083, 'eval_wer': 0.19715994020926755, 'eval_runtime': 79.4519, 'eval_samples_per_second': 35.518, 'eval_steps_per_second': 2.97, 'epoch': 6.37}
+
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 40%|████      | 4000/10000 [1:08:34<1:15:15,  1.33it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6441554427146912, 'eval_wer': 0.19338565022421525, 'eval_runtime': 80.6733, 'eval_samples_per_second': 34.981, 'eval_steps_per_second': 2.925, 'epoch': 7.43}
+{'loss': 0.5147, 'learning_rate': 6.670000000000001e-05, 'epoch': 8.49}
+
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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-3000] due to args.save_total_limit
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 45%|████▌     | 4500/10000 [1:17:36<2:02:14,  1.33s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6793447732925415, 'eval_wer': 0.19495515695067264, 'eval_runtime': 80.545, 'eval_samples_per_second': 35.036, 'eval_steps_per_second': 2.93, 'epoch': 8.49}
+
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 50%|█████     | 5000/10000 [1:26:17<43:24,  1.92it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6431596875190735, 'eval_wer': 0.19200298953662182, 'eval_runtime': 83.1308, 'eval_samples_per_second': 33.947, 'eval_steps_per_second': 2.839, 'epoch': 9.55}
+{'loss': 0.4566, 'learning_rate': 5.558888888888889e-05, 'epoch': 10.62}
+
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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-4000] due to args.save_total_limit
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6605134010314941, 'eval_wer': 0.1853139013452915, 'eval_runtime': 80.2378, 'eval_samples_per_second': 35.17, 'eval_steps_per_second': 2.941, 'epoch': 10.62}
+
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 60%|██████    | 6000/10000 [1:43:33<23:17,  2.86it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6392588019371033, 'eval_wer': 0.18658445440956653, 'eval_runtime': 78.2211, 'eval_samples_per_second': 36.077, 'eval_steps_per_second': 3.017, 'epoch': 11.68}
+{'loss': 0.4155, 'learning_rate': 4.448888888888889e-05, 'epoch': 12.74}
+
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+
                                                 

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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-5000] due to args.save_total_limit
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6917754411697388, 'eval_wer': 0.18030642750373693, 'eval_runtime': 78.1406, 'eval_samples_per_second': 36.114, 'eval_steps_per_second': 3.02, 'epoch': 12.74}
+
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 70%|███████   | 7000/10000 [2:00:48<1:09:36,  1.39s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6514243483543396, 'eval_wer': 0.17911061285500748, 'eval_runtime': 78.7289, 'eval_samples_per_second': 35.845, 'eval_steps_per_second': 2.998, 'epoch': 13.8}
+{'loss': 0.372, 'learning_rate': 3.337777777777778e-05, 'epoch': 14.86}
+
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+
                                                 

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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-6000] due to args.save_total_limit
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.7009950876235962, 'eval_wer': 0.1851270553064275, 'eval_runtime': 78.8286, 'eval_samples_per_second': 35.799, 'eval_steps_per_second': 2.994, 'epoch': 14.86}
+
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 80%|████████  | 8000/10000 [2:18:12<25:30,  1.31it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6824212670326233, 'eval_wer': 0.17858744394618833, 'eval_runtime': 79.8558, 'eval_samples_per_second': 35.339, 'eval_steps_per_second': 2.955, 'epoch': 15.92}
+{'loss': 0.3368, 'learning_rate': 2.2277777777777778e-05, 'epoch': 16.99}
+
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+
                                                 

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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-7000] due to args.save_total_limit
+
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 85%|████████▌ | 8500/10000 [2:27:04<23:59,  1.04it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.6895105838775635, 'eval_wer': 0.1780269058295964, 'eval_runtime': 81.107, 'eval_samples_per_second': 34.794, 'eval_steps_per_second': 2.91, 'epoch': 16.99}
+
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 90%|█████████ | 9000/10000 [2:35:37<13:49,  1.21it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.7150452136993408, 'eval_wer': 0.17589686098654708, 'eval_runtime': 79.9454, 'eval_samples_per_second': 35.299, 'eval_steps_per_second': 2.952, 'epoch': 18.05}
+{'loss': 0.3244, 'learning_rate': 1.1177777777777779e-05, 'epoch': 19.11}
+
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+
                                                 

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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-8000] due to args.save_total_limit
+
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+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.7141156792640686, 'eval_wer': 0.17589686098654708, 'eval_runtime': 85.0058, 'eval_samples_per_second': 33.198, 'eval_steps_per_second': 2.776, 'epoch': 19.11}
+
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100%|██████████| 10000/10000 [2:53:18<00:00,  1.28s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+{'eval_loss': 0.7225230932235718, 'eval_wer': 0.17556053811659192, 'eval_runtime': 77.8748, 'eval_samples_per_second': 36.238, 'eval_steps_per_second': 3.031, 'epoch': 20.17}
+{'loss': 0.2981, 'learning_rate': 6.666666666666667e-08, 'epoch': 21.23}
+
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+
                                                 

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                                                 Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-10000/preprocessor_config.json
+Deleting older checkpoint [experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/checkpoint-9000] due to args.save_total_limit
+
+
+Training completed. Do not forget to share your model on huggingface.co/models =)
+
+
+
                                                       

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+Saving model checkpoint to experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/
+Configuration saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/config.json
+Model weights saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/pytorch_model.bin
+Feature extractor saved in experiments/results/bs_exp/linear/wav2vec2-large-960h-lv60-self/uwb_atcc/0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc/preprocessor_config.json
+{'eval_loss': 0.7286972403526306, 'eval_wer': 0.17556053811659192, 'eval_runtime': 78.6838, 'eval_samples_per_second': 35.865, 'eval_steps_per_second': 2.999, 'epoch': 21.23}
+{'train_runtime': 10488.9956, 'train_samples_per_second': 22.881, 'train_steps_per_second': 0.953, 'train_loss': 0.6986962738037109, 'epoch': 21.23}
+***** train metrics *****
+  epoch                    =      21.23
+  train_loss               =     0.6987
+  train_runtime            = 2:54:48.99
+  train_samples            =      11291
+  train_samples_per_second =     22.881
+  train_steps_per_second   =      0.953
+11/28/2022 18:11:22 - INFO - __main__ - *** Evaluate ***
+The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`,  you can safely ignore this message.
+***** Running Evaluation *****
+  Num examples = 2822
+  Batch size = 12
+
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+Dropping the following result as it does not have all the necessary fields:
+{'metrics': [{'name': 'Wer', 'type': 'wer', 'value': 0.17556053811659192}]}
+***** eval metrics *****
+  epoch                   =      21.23
+  eval_loss               =     0.7287
+  eval_runtime            = 0:01:20.35
+  eval_samples            =       2822
+  eval_samples_per_second =     35.119
+  eval_steps_per_second   =      2.937
+  eval_wer                =     0.1756
+# Accounting: time=10829 threads=1
+# Finished at Mon 28 Nov 18:12:44 CET 2022 with status 0