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0%| | 0/1000 [00:00<?, ?it/s]/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py:2974: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
checkpoint_rng_state = torch.load(rng_file)
Reading metadata...: 75336it [00:02, 29074.31it/s]
Reading metadata...: 13630it [00:00, 14208.60it/s]
[INFO|trainer_utils.py:830] 2024-10-07 10:22:46,488 >> The following columns in the training set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`, you can safely ignore this message.
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/torch/utils/checkpoint.py:295: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead.
with torch.enable_grad(), device_autocast_ctx, torch.cpu.amp.autocast(**ctx.cpu_autocast_kwargs): # type: ignore[attr-defined]
9001it [00:15, 576.66it/s] [INFO|trainer.py:3738] 2024-10-07 10:22:49,598 >> Saving model checkpoint to ./checkpoint-9001
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/modeling_utils.py:2774: UserWarning: Moving the following attributes in the config to the generation config: {'max_length': 448, 'begin_suppress_tokens': [220, 50257]}. You are seeing this warning because you've set generation parameters in the model config, as opposed to in the generation config.
warnings.warn(
[INFO|configuration_utils.py:410] 2024-10-07 10:22:49,601 >> Configuration saved in ./checkpoint-9001/config.json
[INFO|configuration_utils.py:868] 2024-10-07 10:22:49,602 >> Configuration saved in ./checkpoint-9001/generation_config.json
[INFO|modeling_utils.py:3000] 2024-10-07 10:22:55,796 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at ./checkpoint-9001/model.safetensors.index.json.
[INFO|feature_extraction_utils.py:435] 2024-10-07 10:22:55,797 >> Feature extractor saved in ./checkpoint-9001/preprocessor_config.json
9001it [00:25, 576.66it/s][INFO|feature_extraction_utils.py:435] 2024-10-07 10:23:19,205 >> Feature extractor saved in ./preprocessor_config.json
[INFO|trainer.py:2532] 2024-10-07 10:23:19,229 >>
Training completed. Do not forget to share your model on huggingface.co/models =)
[INFO|trainer.py:2770] 2024-10-07 10:23:19,230 >> Loading best model from ./checkpoint-9000 (score: 7.215361500971087).
[WARNING|trainer.py:2892] 2024-10-07 10:23:25,170 >> There were missing keys in the checkpoint model loaded: ['proj_out.weight'].
9001it [00:51, 175.86it/s]
{'train_runtime': 52.4848, 'train_samples_per_second': 304.85, 'train_steps_per_second': 19.053, 'train_loss': 7.723795109133682e-07, 'epoch': 9.0}
[INFO|trainer.py:4519] 2024-10-07 10:23:25,172 >> Waiting for the current checkpoint push to be finished, this might take a couple of minutes.
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py:3889: UserWarning: It seems that you are about to commit a data file (.venv/lib/python3.12/site-packages/pyarrow/tests/data/parquet/v0.7.1.all-named-index.parquet) to a model repository. You are sure this is intended? If you are trying to upload a dataset, please set `repo_type='dataset'` or `--repo-type=dataset` in a CLI.
warnings.warn(
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py:3889: UserWarning: It seems that you are about to commit a data file (.venv/lib/python3.12/site-packages/pyarrow/tests/data/parquet/v0.7.1.column-metadata-handling.parquet) to a model repository. You are sure this is intended? If you are trying to upload a dataset, please set `repo_type='dataset'` or `--repo-type=dataset` in a CLI.
warnings.warn(
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py:3889: UserWarning: It seems that you are about to commit a data file (.venv/lib/python3.12/site-packages/pyarrow/tests/data/parquet/v0.7.1.parquet) to a model repository. You are sure this is intended? If you are trying to upload a dataset, please set `repo_type='dataset'` or `--repo-type=dataset` in a CLI.
warnings.warn(
/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/huggingface_hub/hf_api.py:3889: UserWarning: It seems that you are about to commit a data file (.venv/lib/python3.12/site-packages/pyarrow/tests/data/parquet/v0.7.1.some-named-index.parquet) to a model repository. You are sure this is intended? If you are trying to upload a dataset, please set `repo_type='dataset'` or `--repo-type=dataset` in a CLI.
warnings.warn(
Traceback (most recent call last):
File "/home/tknika/whisper-large-eu/run_speech_recognition_seq2seq_streaming.py", line 630, in <module>
main()
File "/home/tknika/whisper-large-eu/run_speech_recognition_seq2seq_streaming.py", line 579, in main
train_result = trainer.train(resume_from_checkpoint=checkpoint)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2070, in train
return inner_training_loop(
^^^^^^^^^^^^^^^^^^^^
File "/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 2579, in _inner_training_loop
self._finish_current_push()
File "/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/trainer.py", line 4520, in _finish_current_push
self.push_in_progress.wait_until_done()
File "/home/tknika/whisper-large-eu/.venv/lib/python3.12/site-packages/transformers/utils/hub.py", line 1305, in wait_until_done
futures.wait(self.jobs)
File "/usr/lib/python3.12/concurrent/futures/_base.py", line 305, in wait
waiter.event.wait(timeout)
File "/usr/lib/python3.12/threading.py", line 655, in wait
signaled = self._cond.wait(timeout)
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/lib/python3.12/threading.py", line 355, in wait
waiter.acquire()
KeyboardInterrupt
Exception ignored in: <module 'threading' from '/usr/lib/python3.12/threading.py'>
Traceback (most recent call last):
File "/usr/lib/python3.12/threading.py", line 1592, in _shutdown
atexit_call()
File "/usr/lib/python3.12/concurrent/futures/thread.py", line 31, in _python_exit
t.join()
File "/usr/lib/python3.12/threading.py", line 1147, in join
self._wait_for_tstate_lock()
File "/usr/lib/python3.12/threading.py", line 1167, in _wait_for_tstate_lock
if lock.acquire(block, timeout):
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
KeyboardInterrupt:
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