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--- |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/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-base-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: mozilla-foundation/common_voice_17_0 id |
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type: mozilla-foundation/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: 0.1183813634043343 |
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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-base-common_voice_17_0-id |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_17_0 id dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1441 |
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- Wer: 0.1184 |
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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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| 0.3523 | 0.4229 | 1000 | 0.3129 | 0.2365 | |
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| 0.3002 | 0.8458 | 2000 | 0.2391 | 0.1964 | |
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| 0.1718 | 1.2688 | 3000 | 0.2049 | 0.1659 | |
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| 0.1537 | 1.6917 | 4000 | 0.1817 | 0.1516 | |
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| 0.0807 | 2.1146 | 5000 | 0.1643 | 0.1499 | |
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| 0.089 | 2.5375 | 6000 | 0.1562 | 0.1348 | |
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| 0.0883 | 2.9605 | 7000 | 0.1452 | 0.1268 | |
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| 0.0368 | 3.3834 | 8000 | 0.1446 | 0.1324 | |
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| 0.0463 | 3.8063 | 9000 | 0.1401 | 0.1286 | |
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| 0.0278 | 4.2292 | 10000 | 0.1436 | 0.1181 | |
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| 0.0157 | 4.6521 | 11000 | 0.1406 | 0.1125 | |
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| 0.0201 | 5.0751 | 12000 | 0.1392 | 0.1144 | |
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| 0.0121 | 5.4980 | 13000 | 0.1405 | 0.1129 | |
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| 0.0074 | 5.9209 | 14000 | 0.1385 | 0.1195 | |
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| 0.0064 | 6.3438 | 15000 | 0.1410 | 0.1115 | |
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| 0.0066 | 6.7668 | 16000 | 0.1415 | 0.1184 | |
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| 0.0029 | 7.1897 | 17000 | 0.1426 | 0.1190 | |
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| 0.0024 | 7.6126 | 18000 | 0.1429 | 0.1178 | |
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| 0.0021 | 8.0355 | 19000 | 0.1434 | 0.1180 | |
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| 0.0018 | 8.4584 | 20000 | 0.1441 | 0.1184 | |
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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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