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--- |
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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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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: kyrgyz_asr |
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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: ky |
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split: None |
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args: ky |
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metrics: |
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- name: Wer |
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type: wer |
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value: 38.50746268656716 |
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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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# kyrgyz_asr |
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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: 0.3324 |
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- Wer: 38.5075 |
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## Model description |
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This is a test fine-tuning of Whisper Tiny for the Kyrgyz language using a dataset from the Mozilla Foundation. The code is taken from [this source](https://astanahub.com/en/blog/obuchaem-whisper-small-dlia-raspoznavaniia-kazakhskoi-rechi). |
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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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mozilla-foundation/common_voice_17_0 (ky - kyrgyz) |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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- 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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| 0.59 | 0.4735 | 1000 | 0.5917 | 60.8051 | |
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| 0.4987 | 0.9470 | 2000 | 0.4195 | 47.8517 | |
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| 0.3932 | 1.4205 | 3000 | 0.3561 | 42.6685 | |
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| 0.3441 | 1.8939 | 4000 | 0.3324 | 38.5075 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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