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01/31/2022 11:15:19 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1distributed training: False, 16-bits training: True
01/31/2022 11:15:19 - INFO - __main__ - Training/evaluation parameters TrainingArguments(
_n_gpu=1,
adafactor=False,
adam_beta1=0.9,
adam_beta2=0.999,
adam_epsilon=1e-08,
bf16=False,
bf16_full_eval=False,
dataloader_drop_last=False,
dataloader_num_workers=0,
dataloader_pin_memory=True,
ddp_bucket_cap_mb=None,
ddp_find_unused_parameters=None,
debug=[],
deepspeed=None,
disable_tqdm=False,
do_eval=True,
do_predict=False,
do_train=True,
eval_accumulation_steps=None,
eval_steps=500,
evaluation_strategy=IntervalStrategy.STEPS,
fp16=True,
fp16_backend=auto,
fp16_full_eval=False,
fp16_opt_level=O1,
gradient_accumulation_steps=4,
gradient_checkpointing=True,
greater_is_better=None,
group_by_length=True,
half_precision_backend=auto,
hub_model_id=None,
hub_strategy=HubStrategy.EVERY_SAVE,
hub_token=<HUB_TOKEN>,
ignore_data_skip=False,
label_names=None,
label_smoothing_factor=0.0,
learning_rate=7.5e-05,
length_column_name=input_length,
load_best_model_at_end=False,
local_rank=-1,
log_level=-1,
log_level_replica=-1,
log_on_each_node=True,
logging_dir=./runs/Jan31_11-15-19_job-aa543290-d6de-4d4d-8a32-2149b1b8e7e3,
logging_first_step=False,
logging_nan_inf_filter=True,
logging_steps=100,
logging_strategy=IntervalStrategy.STEPS,
lr_scheduler_type=SchedulerType.LINEAR,
max_grad_norm=1.0,
max_steps=-1,
metric_for_best_model=None,
mp_parameters=,
no_cuda=False,
num_train_epochs=50.0,
optim=OptimizerNames.ADAMW_HF,
output_dir=./,
overwrite_output_dir=True,
past_index=-1,
per_device_eval_batch_size=8,
per_device_train_batch_size=8,
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>,
remove_unused_columns=True,
report_to=[],
resume_from_checkpoint=None,
run_name=./,
save_on_each_node=False,
save_steps=500,
save_strategy=IntervalStrategy.STEPS,
save_total_limit=3,
seed=42,
sharded_ddp=[],
skip_memory_metrics=True,
tf32=None,
tpu_metrics_debug=False,
tpu_num_cores=None,
use_legacy_prediction_loop=False,
warmup_ratio=0.0,
warmup_steps=2000,
weight_decay=0.0,
xpu_backend=None,
)
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Downloading and preparing dataset zeroth_korean_asr/clean to /workspace/.cache/huggingface/datasets/kresnik___zeroth_korean_asr/clean/1.0.1/f6cf96a53d5512525e3113bab8048d36ce268658d6e0c40d45f65dfa3f0bc343...
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Dataset zeroth_korean_asr downloaded and prepared to /workspace/.cache/huggingface/datasets/kresnik___zeroth_korean_asr/clean/1.0.1/f6cf96a53d5512525e3113bab8048d36ce268658d6e0c40d45f65dfa3f0bc343. Subsequent calls will reuse this data.
01/31/2022 11:19:02 - WARNING - datasets.builder - Reusing dataset zeroth_korean_asr (/workspace/.cache/huggingface/datasets/kresnik___zeroth_korean_asr/clean/1.0.1/f6cf96a53d5512525e3113bab8048d36ce268658d6e0c40d45f65dfa3f0bc343)
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https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/config.json not found in cache or force_download set to True, downloading to /workspace/.cache/huggingface/transformers/tmpf6f8pfrp
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storing https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/config.json in cache at /workspace/.cache/huggingface/transformers/19f816c26d6fef49a4dfc0fc6b841c37792a250d2697d8432769f8af5698f1dc.90dd5f300087b6277c408283c36aefa2efb15afd0d3e210b3a7c3f3efc478d03
creating metadata file for /workspace/.cache/huggingface/transformers/19f816c26d6fef49a4dfc0fc6b841c37792a250d2697d8432769f8af5698f1dc.90dd5f300087b6277c408283c36aefa2efb15afd0d3e210b3a7c3f3efc478d03
loading configuration file https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/config.json from cache at /workspace/.cache/huggingface/transformers/19f816c26d6fef49a4dfc0fc6b841c37792a250d2697d8432769f8af5698f1dc.90dd5f300087b6277c408283c36aefa2efb15afd0d3e210b3a7c3f3efc478d03
Model config Wav2Vec2Config {
"_name_or_path": "facebook/wav2vec2-xls-r-1b",
"activation_dropout": 0.0,
"adapter_kernel_size": 3,
"adapter_stride": 2,
"add_adapter": false,
"apply_spec_augment": true,
"architectures": [
"Wav2Vec2ForPreTraining"
],
"attention_dropout": 0.1,
"bos_token_id": 1,
"classifier_proj_size": 256,
"codevector_dim": 1024,
"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": 0.0,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout": 0.1,
"hidden_size": 1280,
"initializer_range": 0.02,
"intermediate_size": 5120,
"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": 0.075,
"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": 48,
"num_negatives": 100,
"output_hidden_size": 1280,
"pad_token_id": 0,
"proj_codevector_dim": 1024,
"tdnn_dilation": [
1,
2,
3,
1,
1
],
"tdnn_dim": [
512,
512,
512,
512,
1500
],
"tdnn_kernel": [
5,
3,
3,
1,
1
],
"torch_dtype": "float32",
"transformers_version": "4.17.0.dev0",
"use_weighted_layer_sum": false,
"vocab_size": 32,
"xvector_output_dim": 512
}
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file ./config.json not found
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 https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/config.json from cache at /workspace/.cache/huggingface/transformers/19f816c26d6fef49a4dfc0fc6b841c37792a250d2697d8432769f8af5698f1dc.90dd5f300087b6277c408283c36aefa2efb15afd0d3e210b3a7c3f3efc478d03
Model config Wav2Vec2Config {
"_name_or_path": "facebook/wav2vec2-xls-r-1b",
"activation_dropout": 0.0,
"adapter_kernel_size": 3,
"adapter_stride": 2,
"add_adapter": false,
"apply_spec_augment": true,
"architectures": [
"Wav2Vec2ForPreTraining"
],
"attention_dropout": 0.1,
"bos_token_id": 1,
"classifier_proj_size": 256,
"codevector_dim": 1024,
"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": 0.0,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout": 0.1,
"hidden_size": 1280,
"initializer_range": 0.02,
"intermediate_size": 5120,
"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": 0.075,
"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": 48,
"num_negatives": 100,
"output_hidden_size": 1280,
"pad_token_id": 0,
"proj_codevector_dim": 1024,
"tdnn_dilation": [
1,
2,
3,
1,
1
],
"tdnn_dim": [
512,
512,
512,
512,
1500
],
"tdnn_kernel": [
5,
3,
3,
1,
1
],
"torch_dtype": "float32",
"transformers_version": "4.17.0.dev0",
"use_weighted_layer_sum": false,
"vocab_size": 32,
"xvector_output_dim": 512
}
https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/preprocessor_config.json not found in cache or force_download set to True, downloading to /workspace/.cache/huggingface/transformers/tmpjxesrf60
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creating metadata file for /workspace/.cache/huggingface/transformers/a33f3a17d64af3dc7d6af9fe68e6fcbe153fd601b94de9e09ff27c6916beed02.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326
loading feature extractor configuration file https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/preprocessor_config.json from cache at /workspace/.cache/huggingface/transformers/a33f3a17d64af3dc7d6af9fe68e6fcbe153fd601b94de9e09ff27c6916beed02.d4484dc1c81456a2461485e7168b04347a7b9a4e3b1ef3aba723323b33e12326
Feature extractor Wav2Vec2FeatureExtractor {
"do_normalize": true,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0,
"return_attention_mask": true,
"sampling_rate": 16000
}
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storing https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/pytorch_model.bin in cache at /workspace/.cache/huggingface/transformers/1b10cc2ca6452defe09996da7c9e2d4a9550e22295550c3659e8b1895c97921a.46e33ebecb25f07f270ccfa8896911dd7aeba6b646f8724d18117987926c98db
creating metadata file for /workspace/.cache/huggingface/transformers/1b10cc2ca6452defe09996da7c9e2d4a9550e22295550c3659e8b1895c97921a.46e33ebecb25f07f270ccfa8896911dd7aeba6b646f8724d18117987926c98db
loading weights file https://huggingface.co/facebook/wav2vec2-xls-r-1b/resolve/main/pytorch_model.bin from cache at /workspace/.cache/huggingface/transformers/1b10cc2ca6452defe09996da7c9e2d4a9550e22295550c3659e8b1895c97921a.46e33ebecb25f07f270ccfa8896911dd7aeba6b646f8724d18117987926c98db
Some weights of the model checkpoint at facebook/wav2vec2-xls-r-1b were not used when initializing Wav2Vec2ForCTC: ['project_q.weight', 'project_hid.weight', 'quantizer.codevectors', 'project_q.bias', 'project_hid.bias', 'quantizer.weight_proj.weight', 'quantizer.weight_proj.bias']
- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-1b and are newly initialized: ['lm_head.bias', 'lm_head.weight']
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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Configuration saved in ./preprocessor_config.json
tokenizer config file saved in ./tokenizer_config.json
Special tokens file saved in ./special_tokens_map.json
added tokens file saved in ./added_tokens.json
Configuration saved in ./config.json
loading feature extractor configuration file ./preprocessor_config.json
loading configuration file ./config.json
Model config Wav2Vec2Config {
"_name_or_path": "./",
"activation_dropout": 0.1,
"adapter_kernel_size": 3,
"adapter_stride": 2,
"add_adapter": false,
"apply_spec_augment": true,
"architectures": [
"Wav2Vec2ForPreTraining"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"classifier_proj_size": 256,
"codevector_dim": 1024,
"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": 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": 0.0,
"feat_quantizer_dropout": 0.0,
"final_dropout": 0.0,
"hidden_act": "gelu",
"hidden_dropout": 0.0,
"hidden_size": 1280,
"initializer_range": 0.02,
"intermediate_size": 5120,
"layer_norm_eps": 1e-05,
"layerdrop": 0.0,
"mask_feature_length": 64,
"mask_feature_min_masks": 0,
"mask_feature_prob": 0.25,
"mask_time_length": 10,
"mask_time_min_masks": 2,
"mask_time_prob": 0.75,
"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": 48,
"num_negatives": 100,
"output_hidden_size": 1280,
"pad_token_id": 1204,
"proj_codevector_dim": 1024,
"tdnn_dilation": [
1,
2,
3,
1,
1
],
"tdnn_dim": [
512,
512,
512,
512,
1500
],
"tdnn_kernel": [
5,
3,
3,
1,
1
],
"torch_dtype": "float32",
"transformers_version": "4.17.0.dev0",
"use_weighted_layer_sum": false,
"vocab_size": 1207,
"xvector_output_dim": 512
}
loading feature extractor configuration file ./preprocessor_config.json
Feature extractor Wav2Vec2FeatureExtractor {
"do_normalize": true,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0,
"return_attention_mask": true,
"sampling_rate": 16000
}
Didn't find file ./tokenizer.json. We won't load it.
loading file ./vocab.json
loading file ./tokenizer_config.json
loading file ./added_tokens.json
loading file ./special_tokens_map.json
loading file None
Adding <s> to the vocabulary
Adding </s> to the vocabulary
/workspace/wav2vec2-xls-r-1b-korean/./ is already a clone of https://huggingface.co/anantoj/wav2vec2-xls-r-1b-korean. Make sure you pull the latest changes with `repo.git_pull()`.
01/31/2022 11:22:37 - WARNING - huggingface_hub.repository - /workspace/wav2vec2-xls-r-1b-korean/./ is already a clone of https://huggingface.co/anantoj/wav2vec2-xls-r-1b-korean. Make sure you pull the latest changes with `repo.git_pull()`.
Using 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.
/opt/conda/lib/python3.8/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use thePyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning
warnings.warn(
***** Running training *****
Num examples = 22262
Num Epochs = 50
Instantaneous batch size per device = 8
Total train batch size (w. parallel, distributed & accumulation) = 32
Gradient Accumulation steps = 4
Total optimization steps = 34750
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1%|β | 500/34750 [45:49<31:05:46, 3.27s/it]
1%|β | 500/34750 [45:49<31:05:46, 3.27s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.
***** Running Evaluation *****
Num examples = 456
Batch size = 8
{'loss': 27.8845, 'learning_rate': 3.6e-06, 'epoch': 0.14}
{'loss': 5.2607, 'learning_rate': 7.35e-06, 'epoch': 0.29}
{'loss': 4.8397, 'learning_rate': 1.1099999999999999e-05, 'epoch': 0.43}
{'loss': 4.6751, 'learning_rate': 1.485e-05, 'epoch': 0.57}
{'loss': 4.603, 'learning_rate': 1.8599999999999998e-05, 'epoch': 0.72}
0%| | 0/57 [00:00<?, ?it/s][A
4%|β | 2/57 [00:01<00:27, 1.98it/s][A
5%|β | 3/57 [00:01<00:36, 1.49it/s][A
7%|β | 4/57 [00:02<00:41, 1.28it/s][A
9%|β | 5/57 [00:03<00:41, 1.26it/s][A
11%|β | 6/57 [00:04<00:44, 1.15it/s][A
12%|ββ | 7/57 [00:05<00:44, 1.12it/s][A
14%|ββ | 8/57 [00:06<00:45, 1.08it/s][A
16%|ββ | 9/57 [00:07<00:43, 1.09it/s][A
18%|ββ | 10/57 [00:08<00:42, 1.10it/s][A
19%|ββ | 11/57 [00:09<00:43, 1.05it/s][A
21%|ββ | 12/57 [00:10<00:45, 1.01s/it][A
23%|βββ | 13/57 [00:11<00:47, 1.08s/it][A
25%|βββ | 14/57 [00:12<00:46, 1.09s/it][A
26%|βββ | 15/57 [00:14<00:47, 1.13s/it][A
28%|βββ | 16/57 [00:15<00:46, 1.14s/it][A
30%|βββ | 17/57 [00:16<00:45, 1.14s/it][A
32%|ββββ | 18/57 [00:17<00:42, 1.10s/it][A
33%|ββββ | 19/57 [00:18<00:42, 1.11s/it][A
35%|ββββ | 20/57 [00:19<00:40, 1.08s/it][A
37%|ββββ | 21/57 [00:20<00:39, 1.09s/it][A
39%|ββββ | 22/57 [00:22<00:39, 1.12s/it][A
40%|ββββ | 23/57 [00:22<00:35, 1.06s/it][A
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44%|βββββ | 25/57 [00:24<00:30, 1.06it/s][A
46%|βββββ | 26/57 [00:25<00:26, 1.17it/s][A
47%|βββββ | 27/57 [00:26<00:27, 1.08it/s][A
49%|βββββ | 28/57 [00:27<00:29, 1.01s/it][A
51%|βββββ | 29/57 [00:28<00:31, 1.11s/it][A
53%|ββββββ | 30/57 [00:29<00:29, 1.09s/it][A
54%|ββββββ | 31/57 [00:31<00:30, 1.19s/it][A
56%|ββββββ | 32/57 [00:32<00:27, 1.12s/it][A
58%|ββββββ | 33/57 [00:33<00:27, 1.14s/it][A
60%|ββββββ | 34/57 [00:34<00:26, 1.15s/it][A
61%|βββββββ | 35/57 [00:35<00:24, 1.10s/it][A
63%|βββββββ | 36/57 [00:36<00:23, 1.14s/it][A
65%|βββββββ | 37/57 [00:37<00:19, 1.01it/s][A
67%|βββββββ | 38/57 [00:38<00:19, 1.02s/it][A
68%|βββββββ | 39/57 [00:39<00:17, 1.05it/s][A
70%|βββββββ | 40/57 [00:40<00:17, 1.03s/it][A
72%|ββββββββ | 41/57 [00:41<00:17, 1.07s/it][A
74%|ββββββββ | 42/57 [00:42<00:15, 1.02s/it][A
75%|ββββββββ | 43/57 [00:43<00:13, 1.04it/s][A
77%|ββββββββ | 44/57 [00:44<00:11, 1.10it/s][A
79%|ββββββββ | 45/57 [00:45<00:11, 1.06it/s][A
81%|ββββββββ | 46/57 [00:46<00:10, 1.01it/s][A
82%|βββββββββ | 47/57 [00:47<00:08, 1.13it/s][A
84%|βββββββββ | 48/57 [00:47<00:07, 1.17it/s][A
86%|βββββββββ | 49/57 [00:48<00:06, 1.18it/s][A
88%|βββββββββ | 50/57 [00:49<00:06, 1.13it/s][A
89%|βββββββββ | 51/57 [00:50<00:05, 1.13it/s][A
91%|βββββββββ | 52/57 [00:51<00:04, 1.12it/s][A
93%|ββββββββββ| 53/57 [00:52<00:03, 1.10it/s][A
95%|ββββββββββ| 54/57 [00:53<00:02, 1.18it/s][A
96%|ββββββββββ| 55/57 [00:53<00:01, 1.23it/s][A
98%|ββββββββββ| 56/57 [00:54<00:00, 1.23it/s][A
100%|ββββββββββ| 57/57 [00:55<00:00, 1.17it/s][A
[A
1%|β | 500/34750 [46:51<31:05:46, 3.27s/it]
100%|ββββββββββ| 57/57 [01:00<00:00, 1.17it/s][A
[ASaving model checkpoint to ./checkpoint-500
Configuration saved in ./checkpoint-500/config.json
Model weights saved in ./checkpoint-500/pytorch_model.bin
Configuration saved in ./checkpoint-500/preprocessor_config.json
Configuration saved in ./preprocessor_config.json
|