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--- |
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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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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-common_voice_17_0-id |
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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_17_0 |
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type: common_voice_17_0 |
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config: id |
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split: None |
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args: id |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.1807044410413476 |
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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-common_voice_17_0-id |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2000 |
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- Wer: 0.1807 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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- training_steps: 20000 |
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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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|:-------------:|:------:|:-----:|:---------------:|:------:| |
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| 0.4911 | 0.4229 | 1000 | 0.4546 | 0.3321 | |
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| 0.4078 | 0.8458 | 2000 | 0.3520 | 0.2807 | |
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| 0.2679 | 1.2688 | 3000 | 0.3050 | 0.2421 | |
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| 0.2423 | 1.6917 | 4000 | 0.2725 | 0.2217 | |
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| 0.169 | 2.1146 | 5000 | 0.2515 | 0.2184 | |
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| 0.1646 | 2.5375 | 6000 | 0.2377 | 0.2082 | |
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| 0.1731 | 2.9605 | 7000 | 0.2189 | 0.1911 | |
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| 0.1017 | 3.3834 | 8000 | 0.2135 | 0.1970 | |
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| 0.0985 | 3.8063 | 9000 | 0.2077 | 0.1819 | |
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| 0.0828 | 4.2292 | 10000 | 0.2070 | 0.1792 | |
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| 0.06 | 4.6521 | 11000 | 0.1991 | 0.1826 | |
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| 0.0629 | 5.0751 | 12000 | 0.2012 | 0.1918 | |
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| 0.0545 | 5.4980 | 13000 | 0.2017 | 0.1864 | |
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| 0.0392 | 5.9209 | 14000 | 0.1985 | 0.1910 | |
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| 0.0338 | 6.3438 | 15000 | 0.1989 | 0.1807 | |
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| 0.0312 | 6.7668 | 16000 | 0.1982 | 0.1945 | |
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| 0.0237 | 7.1897 | 17000 | 0.1998 | 0.1842 | |
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| 0.0223 | 7.6126 | 18000 | 0.1994 | 0.1800 | |
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| 0.0192 | 8.0355 | 19000 | 0.1993 | 0.1806 | |
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| 0.0158 | 8.4584 | 20000 | 0.2000 | 0.1807 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.1.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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