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--- |
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language: |
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- ru |
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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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- aangry-mouse/stepik_ml_ru |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Ml Ru |
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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: "ML \u0434\u0430\u0442\u0430\u0441\u0435\u0442" |
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type: aangry-mouse/stepik_ml_ru |
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args: 'config: ru, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 35.272870043188064 |
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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 Ml Ru |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the ML датасет dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4705 |
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- Wer: 35.2729 |
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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: 16 |
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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: 500 |
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- training_steps: 1000 |
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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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| 0.6752 | 0.6649 | 250 | 0.6513 | 39.3404 | |
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| 0.4415 | 1.3298 | 500 | 0.5277 | 38.4923 | |
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| 0.4037 | 1.9947 | 750 | 0.4766 | 35.0766 | |
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| 0.2825 | 2.6596 | 1000 | 0.4705 | 35.2729 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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