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--- |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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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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language: |
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- cy |
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- en |
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pipeline_tag: automatic-speech-recognition |
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datasets: |
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- techiaith/commonvoice_18_0_cy_en |
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--- |
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# whisper-large-v3-ft-cy-en |
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This model is a version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) fine-tuned with a curated collection of |
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Welsh and English speech data (see: [techiaith/commonvoice_18_0_cy_en](https://huggingface.co/datasets/techiaith/commonvoice_18_0_cy_en) |
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collected originally from Mozilla's Common Voice project. |
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It achieves the following results on the following language specific test sets: |
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- WER (test_en): 13.85 |
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- WER (test_cy): 8.78 |
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- WER (test_cy+test_en): 9.55 |
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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: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 4000 |
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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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| 0.2097 | 0.2497 | 1000 | 0.2169 | 14.2221 | |
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| 0.1621 | 0.4993 | 2000 | 0.1816 | 11.6845 | |
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| 0.1406 | 0.7490 | 3000 | 0.1609 | 10.2445 | |
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| 0.1242 | 0.9987 | 4000 | 0.1505 | 9.5594 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
