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uz_asr_transformers_4000

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aslon commited on
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ssl training first epoch commit

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Files changed (24) hide show
  1. __pycache__/common_voice_prepare.cpython-311.pyc +0 -0
  2. __pycache__/infer_2.cpython-311.pyc +0 -0
  3. infer_2.py +16 -2
  4. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/CKPT.yaml +2 -2
  5. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/brain.ckpt +1 -1
  6. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+21-50-40+00}/counter.ckpt +1 -1
  7. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/dataloader-TRAIN.ckpt +2 -2
  8. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+21-50-40+00}/dataloader-VALID.ckpt +1 -1
  9. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/model.ckpt +1 -1
  10. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/noam_scheduler.ckpt +1 -1
  11. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/normalizer.ckpt +1 -1
  12. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/optimizer.ckpt +1 -1
  13. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+21-50-40+00}/scaler.ckpt +1 -1
  14. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/CKPT.yaml +1 -1
  15. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/brain.ckpt +1 -1
  16. model_saved/save/{CKPT+2025-02-12+09-16-43+00 → CKPT+2025-02-23+23-55-10+00}/counter.ckpt +1 -1
  17. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/dataloader-TRAIN.ckpt +1 -1
  18. model_saved/save/CKPT+2025-02-23+23-55-10+00/dataloader-VALID.ckpt +3 -0
  19. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/model.ckpt +1 -1
  20. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/noam_scheduler.ckpt +1 -1
  21. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/normalizer.ckpt +1 -1
  22. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/optimizer.ckpt +1 -1
  23. model_saved/save/{CKPT+2025-02-22+08-52-02+00 → CKPT+2025-02-23+23-55-10+00}/scaler.ckpt +1 -1
  24. model_saved/train_log.txt +2 -2
__pycache__/common_voice_prepare.cpython-311.pyc CHANGED
Binary files a/__pycache__/common_voice_prepare.cpython-311.pyc and b/__pycache__/common_voice_prepare.cpython-311.pyc differ
 
__pycache__/infer_2.cpython-311.pyc CHANGED
Binary files a/__pycache__/infer_2.cpython-311.pyc and b/__pycache__/infer_2.cpython-311.pyc differ
 
infer_2.py CHANGED
@@ -42,6 +42,12 @@ from collections import defaultdict
42
  logger = structlog.get_logger(__name__)
43
 
44
 
 
 
 
 
 
 
45
  def timer(func):
46
  """Decorator to measure the execution time of a function."""
47
 
@@ -325,7 +331,9 @@ class ASR(sb.core.Brain):
325
  if current_epoch % valid_search_interval == 0 or stage == sb.Stage.TEST:
326
  stage_stats["WER"] = self.wer_metric.summarize("error_rate")
327
  stage_stats["CER"] = self.cer_metric.summarize("error_rate")
328
-
 
 
329
  # log stats and save checkpoint at end-of-epoch
330
  if stage == sb.Stage.VALID:
331
  # report different epoch stages according current stage
@@ -543,6 +551,10 @@ class TransformerPretrainedASR(ASR):
543
  # ):
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  # break
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546
  def _fit_train(self, train_set, unlabeled_train_set, epoch, enable):
547
  # Training stage
548
  self.on_stage_start(Stage.TRAIN, epoch)
@@ -578,7 +590,9 @@ class TransformerPretrainedASR(ASR):
578
  loss = self.fit_batch(batch, batch_unlabeled)
579
  self.avg_train_loss = self.update_average(loss, self.avg_train_loss)
580
  t.set_postfix(train_loss=self.avg_train_loss)
581
-
 
 
582
  if self.profiler is not None:
583
  self.profiler.step()
584
  if self.profiler.step_num > self.tot_prof_steps:
 
42
  logger = structlog.get_logger(__name__)
43
 
44
 
45
+ # Initialize file logger
46
+ def log_step_to_file(message):
47
+ with open("training_log.log", "a") as f:
48
+ f.write(message + "\n")
49
+
50
+
51
  def timer(func):
52
  """Decorator to measure the execution time of a function."""
53
 
 
331
  if current_epoch % valid_search_interval == 0 or stage == sb.Stage.TEST:
332
  stage_stats["WER"] = self.wer_metric.summarize("error_rate")
333
  stage_stats["CER"] = self.cer_metric.summarize("error_rate")
334
+ log_step_to_file(
335
+ f"Epoch {epoch}, WER: {stage_stats['WER']}, CER: {stage_stats['CER']}, ACC: {stage_stats['ACC']}"
336
+ )
337
  # log stats and save checkpoint at end-of-epoch
338
  if stage == sb.Stage.VALID:
339
  # report different epoch stages according current stage
 
551
  # ):
552
  # break
553
 
554
+ def log_step_to_file(self, message):
555
+ with open("training_log.log", "a") as f:
556
+ f.write(message)
557
+
558
  def _fit_train(self, train_set, unlabeled_train_set, epoch, enable):
559
  # Training stage
560
  self.on_stage_start(Stage.TRAIN, epoch)
 
590
  loss = self.fit_batch(batch, batch_unlabeled)
591
  self.avg_train_loss = self.update_average(loss, self.avg_train_loss)
592
  t.set_postfix(train_loss=self.avg_train_loss)
593
+ log_step_to_file(
594
+ f"Epoch {epoch}, Train Step {self.step}, Train Loss: {self.avg_train_loss}"
595
+ )
596
  if self.profiler is not None:
597
  self.profiler.step()
598
  if self.profiler.step_num > self.tot_prof_steps:
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