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--- |
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library_name: transformers |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-large-v3-turbo-half |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_16_1 |
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type: common_voice_16_1 |
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config: en |
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split: test |
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args: en |
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metrics: |
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- type: wer |
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value: 28.434990232255263 |
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name: Wer |
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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-large-v3-turbo-half |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_16_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7088 |
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- Wer: 28.4350 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| No log | 0 | 0 | 8.8155 | 100.0 | |
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| 0.9071 | 0.1 | 500 | 1.5140 | 64.0547 | |
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| 0.7138 | 0.2 | 1000 | 1.1375 | 49.9023 | |
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| 0.5078 | 0.3 | 1500 | 1.0159 | 41.3067 | |
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| 0.4833 | 0.4 | 2000 | 0.9379 | 34.7081 | |
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| 0.4164 | 0.5 | 2500 | 0.8927 | 30.9746 | |
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| 0.517 | 0.6 | 3000 | 0.8473 | 31.0397 | |
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| 0.33 | 0.7 | 3500 | 0.7714 | 27.1326 | |
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| 0.364 | 0.8 | 4000 | 0.7508 | 25.6132 | |
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| 0.3728 | 0.9 | 4500 | 0.7091 | 24.4628 | |
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| 0.4321 | 1.0 | 5000 | 0.7088 | 28.4350 | |
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### Framework versions |
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- Transformers 4.54.0 |
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- Pytorch 2.8.0.dev20250319+cu128 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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