End of training
Browse files- README.md +19 -6
- all_results.json +13 -0
- eval_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +2932 -0
- wandb/run-20250217_214618-7bygcjmf/files/output.log +158 -0
- wandb/run-20250217_214618-7bygcjmf/run-7bygcjmf.wandb +2 -2
README.md
CHANGED
@@ -3,23 +3,36 @@ library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-tiny
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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-
- name:
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-
results:
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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-
#
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-
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on
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It achieves the following results on the evaluation set:
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-
- Loss: 0.
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- Wer:
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## Model description
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license: apache-2.0
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base_model: openai/whisper-tiny
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tags:
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+
- whisper-event
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- generated_from_trainer
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+
datasets:
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+
- asierhv/composite_corpus_eu_v2.1
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metrics:
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- wer
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model-index:
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+
- name: Whisper Tiny Basque
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results:
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+
- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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+
dataset:
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+
name: asierhv/composite_corpus_eu_v2.1
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+
type: asierhv/composite_corpus_eu_v2.1
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+
metrics:
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+
- name: Wer
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+
type: wer
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+
value: 14.985509956062447
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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+
# Whisper Tiny Basque
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+
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the asierhv/composite_corpus_eu_v2.1 dataset.
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It achieves the following results on the evaluation set:
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+
- Loss: 0.3002
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+
- Wer: 14.9855
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## Model description
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all_results.json
ADDED
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{
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"epoch": 1.0,
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"eval_loss": 0.300187349319458,
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+
"eval_runtime": 56.9322,
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+
"eval_samples_per_second": 36.956,
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+
"eval_steps_per_second": 2.319,
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"eval_wer": 14.985509956062447,
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"total_flos": 7.8780432384e+18,
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"train_loss": 0.24547564173936845,
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+
"train_runtime": 3924.8092,
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+
"train_samples_per_second": 81.533,
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"train_steps_per_second": 2.548
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}
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eval_results.json
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{
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"epoch": 1.0,
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"eval_loss": 0.300187349319458,
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"eval_runtime": 56.9322,
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+
"eval_samples_per_second": 36.956,
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+
"eval_steps_per_second": 2.319,
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"eval_wer": 14.985509956062447
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}
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train_results.json
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{
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"epoch": 1.0,
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"total_flos": 7.8780432384e+18,
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"train_loss": 0.24547564173936845,
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"train_runtime": 3924.8092,
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"train_samples_per_second": 81.533,
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"train_steps_per_second": 2.548
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}
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trainer_state.json
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wandb/run-20250217_214618-7bygcjmf/files/output.log
CHANGED
@@ -1901,3 +1901,161 @@ Training completed. Do not forget to share your model on huggingface.co/models =
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[INFO|feature_extraction_utils.py:437] 2025-02-17 22:51:55,409 >> Feature extractor saved in ./preprocessor_config.json
|
1902 |
[INFO|modelcard.py:449] 2025-02-17 22:51:55,555 >> Dropping the following result as it does not have all the necessary fields:
|
1903 |
{'task': {'name': 'Automatic Speech Recognition', 'type': 'automatic-speech-recognition'}, 'metrics': [{'name': 'Wer', 'type': 'wer', 'value': 15.72403477610545}]}
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1901 |
[INFO|feature_extraction_utils.py:437] 2025-02-17 22:51:55,409 >> Feature extractor saved in ./preprocessor_config.json
|
1902 |
[INFO|modelcard.py:449] 2025-02-17 22:51:55,555 >> Dropping the following result as it does not have all the necessary fields:
|
1903 |
{'task': {'name': 'Automatic Speech Recognition', 'type': 'automatic-speech-recognition'}, 'metrics': [{'name': 'Wer', 'type': 'wer', 'value': 15.72403477610545}]}
|
1904 |
+
***** train metrics *****
|
1905 |
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epoch = 1.0
|
1906 |
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total_flos = 7336999511GF
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1907 |
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train_loss = 0.2455
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train_runtime = 1:05:24.80
|
1909 |
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train_samples_per_second = 81.533
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1910 |
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train_steps_per_second = 2.548
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1911 |
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02/17/2025 22:52:00 - INFO - __main__ - *** Evaluate ***
|
1912 |
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[INFO|trainer.py:4258] 2025-02-17 22:52:00,618 >>
|
1913 |
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***** Running Evaluation *****
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1914 |
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[INFO|trainer.py:4262] 2025-02-17 22:52:00,618 >> Num examples: Unknown
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1915 |
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[INFO|trainer.py:4263] 2025-02-17 22:52:00,618 >> Batch size = 16
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1916 |
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[INFO|trainer_utils.py:837] 2025-02-17 22:52:07,406 >> The following columns in the evaluation 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.
|
1917 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:07,558 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1918 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:07,971 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1919 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:08,460 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1920 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:08,998 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1921 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:09,391 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1922 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:09,739 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1923 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:10,053 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1924 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:10,390 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1925 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:10,747 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1926 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:11,158 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1927 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:11,489 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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1928 |
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:11,920 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:46,992 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:47,301 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:47,584 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:48,146 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:48,450 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:48,741 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:49,038 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:49,299 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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[INFO|generation_whisper.py:1844] 2025-02-17 22:52:49,536 >> Increase max_length from 225 to 228 since input is conditioned on previous segment.
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2049 |
+
***** eval metrics *****
|
2050 |
+
epoch = 1.0
|
2051 |
+
eval_loss = 0.3002
|
2052 |
+
eval_runtime = 0:00:56.93
|
2053 |
+
eval_samples_per_second = 36.956
|
2054 |
+
eval_steps_per_second = 2.319
|
2055 |
+
eval_wer = 14.9855
|
2056 |
+
[INFO|trainer.py:3942] 2025-02-17 22:52:57,551 >> Saving model checkpoint to ./
|
2057 |
+
[INFO|configuration_utils.py:423] 2025-02-17 22:52:57,552 >> Configuration saved in ./config.json
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[INFO|configuration_utils.py:909] 2025-02-17 22:52:57,553 >> Configuration saved in ./generation_config.json
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[INFO|modeling_utils.py:3040] 2025-02-17 22:52:57,945 >> Model weights saved in ./model.safetensors
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[INFO|feature_extraction_utils.py:437] 2025-02-17 22:52:57,947 >> Feature extractor saved in ./preprocessor_config.json
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run-7bygcjmf.wandb: 100%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 4.98M/4.98M [00:01<00:00, 3.58MB/s]
|
wandb/run-20250217_214618-7bygcjmf/run-7bygcjmf.wandb
CHANGED
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size
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oid sha256:7b24350895068d2eeaab4073bdf0d0a76ef0d5ec72269f30f06e8afe5fbb6315
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size 4980736
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