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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-v2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_22_0 |
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metrics: |
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- wer |
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model-index: |
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- name: openai/whisper-large-v2 |
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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_22_0 |
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type: common_voice_22_0 |
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config: eu |
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split: test |
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args: eu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 10.165494624382987 |
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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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# openai/whisper-large-v2 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_22_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2925 |
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- Wer: 10.1655 |
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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: 3.75e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 100000 |
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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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| 0.0113 | 10.8234 | 5000 | 0.2195 | 9.4386 | |
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| 0.008 | 21.6457 | 10000 | 0.2475 | 10.0455 | |
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| 0.0049 | 32.4680 | 15000 | 0.2663 | 10.2737 | |
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| 0.0023 | 43.2904 | 20000 | 0.2671 | 9.6820 | |
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| 0.0019 | 54.1127 | 25000 | 0.2794 | 9.4809 | |
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| 0.0025 | 64.9361 | 30000 | 0.2925 | 10.1655 | |
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### Framework versions |
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- Transformers 4.52.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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