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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: wu-kiot/whisper-small-am-fleurs |
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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-small-fc-am |
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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: am |
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split: None |
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args: am |
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metrics: |
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- name: Wer |
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type: wer |
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value: 62.73062730627307 |
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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-small-fc-am |
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This model is a fine-tuned version of [wu-kiot/whisper-small-am-fleurs](https://huggingface.co/wu-kiot/whisper-small-am-fleurs) 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: 0.3756 |
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- Wer: 62.7306 |
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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: 5e-05 |
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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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- 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: 150 |
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- num_epochs: 5 |
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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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| 0.2866 | 1.0 | 44 | 0.2855 | 63.9958 | |
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| 0.1582 | 2.0 | 88 | 0.2958 | 64.1539 | |
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| 0.0885 | 3.0 | 132 | 0.3311 | 67.4222 | |
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| 0.0793 | 4.0 | 176 | 0.3700 | 66.4207 | |
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| 0.0375 | 5.0 | 220 | 0.3756 | 62.7306 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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