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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-turbo |
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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: whisper-finetuned-fullsample-v1 |
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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: pt |
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split: None |
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args: pt |
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metrics: |
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- name: Wer |
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type: wer |
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value: 11.31198430186737 |
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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-finetuned-fullsample-v1 |
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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_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3719 |
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- Wer: 11.3120 |
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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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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 32 |
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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: 600 |
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- training_steps: 6000 |
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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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| 0.0094 | 8.1384 | 1000 | 0.2714 | 24.2485 | |
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| 0.0008 | 16.2767 | 2000 | 0.3292 | 25.8955 | |
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| 0.0011 | 24.4151 | 3000 | 0.3289 | 12.6679 | |
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| 0.0003 | 32.5534 | 4000 | 0.3546 | 12.0631 | |
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| 0.0015 | 40.6918 | 5000 | 0.3405 | 12.0647 | |
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| 0.0002 | 48.8301 | 6000 | 0.3719 | 11.3120 | |
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### Framework versions |
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- Transformers 4.46.0.dev0 |
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- Pytorch 2.4.1+cu124 |
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- Datasets 3.0.2.dev0 |
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- Tokenizers 0.20.0 |
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