End of training
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README.md
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_6_1
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model-index:
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- name: Whisper Small Frisian 1h
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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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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 6.1 dataset.
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It achieves the following results on the evaluation set:
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- eval_runtime: 596.14
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- eval_samples_per_second: 5.066
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- eval_steps_per_second: 0.634
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- epoch: 7.8652
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- step: 700
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps:
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.40.1
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_6_1
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metrics:
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- wer
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model-index:
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- name: Whisper Small Frisian 1h
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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: Common Voice 6.1
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type: mozilla-foundation/common_voice_6_1
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args: 'config: frisian, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 47.79183746212796
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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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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 6.1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9900
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- Wer: 47.7918
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps: 2000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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| 2.4073 | 1.1236 | 100 | 2.2555 | 82.9549 |
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| 1.5143 | 2.2472 | 200 | 1.6651 | 73.4557 |
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| 1.1865 | 3.3708 | 300 | 1.4237 | 65.1256 |
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| 0.9368 | 4.4944 | 400 | 1.2874 | 59.4832 |
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| 0.8009 | 5.6180 | 500 | 1.1957 | 56.5461 |
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| 0.6722 | 6.7416 | 600 | 1.1345 | 54.6890 |
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| 0.5726 | 7.8652 | 700 | 1.0894 | 53.1919 |
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| 0.5068 | 8.9888 | 800 | 1.0575 | 51.7769 |
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| 0.4239 | 10.1124 | 900 | 1.0351 | 50.8002 |
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| 0.3799 | 11.2360 | 1000 | 1.0197 | 49.9198 |
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| 0.295 | 12.3596 | 1100 | 1.0110 | 49.3673 |
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| 0.2852 | 13.4831 | 1200 | 1.0022 | 48.7507 |
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| 0.2478 | 14.6067 | 1300 | 0.9965 | 48.3800 |
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| 0.2267 | 15.7303 | 1400 | 0.9931 | 48.1911 |
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| 0.1986 | 16.8539 | 1500 | 0.9916 | 48.1412 |
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| 0.1922 | 17.9775 | 1600 | 0.9907 | 47.9558 |
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| 0.1724 | 19.1011 | 1700 | 0.9905 | 47.8703 |
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| 0.1709 | 20.2247 | 1800 | 0.9900 | 47.9059 |
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| 0.1749 | 21.3483 | 1900 | 0.9900 | 47.7598 |
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| 0.145 | 22.4719 | 2000 | 0.9900 | 47.7918 |
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### Framework versions
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- Transformers 4.40.1
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