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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-large-v3 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- honzapucalek/monika_asr |
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metrics: |
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- wer |
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model-index: |
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- name: monika_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: honzapucalek/monika_asr cs |
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type: honzapucalek/monika_asr |
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config: cs |
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split: test |
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args: cs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.26058233423048693 |
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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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# monika_asr |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the honzapucalek/monika_asr cs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7834 |
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- Wer: 0.2606 |
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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: Use 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: 5000 |
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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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| 0.0001 | 45.4545 | 1000 | 0.6877 | 0.2625 | |
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| 0.0001 | 90.9091 | 2000 | 0.6910 | 0.2589 | |
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| 0.0 | 136.3636 | 3000 | 0.7108 | 0.2591 | |
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| 0.0 | 181.8182 | 4000 | 0.7377 | 0.2618 | |
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| 0.0 | 227.2727 | 5000 | 0.7669 | 0.2606 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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