Training in progress, step 4000
Browse files
.ipynb_checkpoints/run_speech_recognition_seq2seq_streaming-checkpoint.py
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@@ -511,7 +511,8 @@ def main():
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# 8. Load Metric
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-
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do_normalize_eval = data_args.do_normalize_eval
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def compute_metrics(pred):
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@@ -527,9 +528,10 @@ 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 *
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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):
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pytorch_model.bin
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 3055754841
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version https://git-lfs.github.com/spec/v1
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oid sha256:74502c29f79feacae7fad9595f99a0a6e3b581b72e0b2c9490ba8016f6deaab6
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size 3055754841
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run_speech_recognition_seq2seq_streaming.py
CHANGED
@@ -511,7 +511,8 @@ def main():
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)
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513 |
# 8. Load Metric
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514 |
-
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do_normalize_eval = data_args.do_normalize_eval
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516 |
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def compute_metrics(pred):
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@@ -527,9 +528,10 @@ 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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529 |
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530 |
-
wer = 100 *
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531 |
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-
return {"wer": wer}
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533 |
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534 |
# 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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512 |
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513 |
# 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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530 |
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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):
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runs/Dec08_05-32-25_132-145-179-103/events.out.tfevents.1670477595.132-145-179-103.68786.0
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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-
size
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:d3086d33316684db3a8233211dd593825bb283af845f99ed1361599b98b4c0dd
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+
size 30583
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