vumichien commited on
Commit
798c92b
1 Parent(s): a9ee210

Training in progress, step 2000

Browse files
.ipynb_checkpoints/run_speech_recognition_seq2seq_streaming-checkpoint.py CHANGED
@@ -503,7 +503,8 @@ def main():
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  )
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  # 8. Load Metric
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- metric = evaluate.load("wer")
 
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  do_normalize_eval = data_args.do_normalize_eval
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  def compute_metrics(pred):
@@ -519,9 +520,9 @@ def main():
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  pred_str = [normalizer(pred) for pred in pred_str]
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  label_str = [normalizer(label) for label in label_str]
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- wer = 100 * metric.compute(predictions=pred_str, references=label_str)
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-
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- return {"wer": wer}
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  # 9. Create a single speech processor
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  if is_main_process(training_args.local_rank):
 
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  )
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  # 8. Load Metric
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+ wer_metric = evaluate.load("wer")
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+ cer_metric = evaluate.load("cer")
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  do_normalize_eval = data_args.do_normalize_eval
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  def compute_metrics(pred):
 
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  pred_str = [normalizer(pred) for pred in pred_str]
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  label_str = [normalizer(label) for label in label_str]
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+ wer = 100 * wer_metric.compute(predictions=pred_str, references=label_str)
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+ cer = 100 * cer_metric.compute(predictions=pred_str, references=label_str)
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+ return {"wer": wer, "cer": cer}
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  # 9. Create a single speech processor
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  if is_main_process(training_args.local_rank):
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
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  size 3055754841
 
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  size 3055754841
run_speech_recognition_seq2seq_streaming.py CHANGED
@@ -503,7 +503,8 @@ def main():
503
  )
504
 
505
  # 8. Load Metric
506
- metric = evaluate.load("wer")
 
507
  do_normalize_eval = data_args.do_normalize_eval
508
 
509
  def compute_metrics(pred):
@@ -519,9 +520,9 @@ def main():
519
  pred_str = [normalizer(pred) for pred in pred_str]
520
  label_str = [normalizer(label) for label in label_str]
521
 
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- wer = 100 * metric.compute(predictions=pred_str, references=label_str)
523
-
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- return {"wer": wer}
525
 
526
  # 9. Create a single speech processor
527
  if is_main_process(training_args.local_rank):
 
503
  )
504
 
505
  # 8. Load Metric
506
+ wer_metric = evaluate.load("wer")
507
+ cer_metric = evaluate.load("cer")
508
  do_normalize_eval = data_args.do_normalize_eval
509
 
510
  def compute_metrics(pred):
 
520
  pred_str = [normalizer(pred) for pred in pred_str]
521
  label_str = [normalizer(label) for label in label_str]
522
 
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+ wer = 100 * wer_metric.compute(predictions=pred_str, references=label_str)
524
+ cer = 100 * cer_metric.compute(predictions=pred_str, references=label_str)
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+ return {"wer": wer, "cer": cer}
526
 
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  # 9. Create a single speech processor
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  if is_main_process(training_args.local_rank):
runs/Dec07_07-28-49_140-238-225-207/events.out.tfevents.1670398176.140-238-225-207.101704.0 CHANGED
@@ -1,3 +1,3 @@
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- size 10789
 
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