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--- |
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language: |
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- ha |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Seon25/common_voice_16_0_ |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Tiny Ha - Eldad Akhaumere |
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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 16.0 |
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type: Seon25/common_voice_16_0_ |
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config: ha |
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split: None |
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args: 'config: ha, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 107.2810883310979 |
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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 Tiny Ha - Eldad Akhaumere |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 16.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5851 |
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- Wer Ortho: 108.4180 |
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- Wer: 107.2811 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 15.0 |
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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 Ortho | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:|:--------:| |
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| 1.3176 | 3.1847 | 500 | 2.1073 | 133.8086 | 132.4392 | |
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| 0.624 | 6.3694 | 1000 | 2.2333 | 110.4492 | 111.1324 | |
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| 0.2135 | 9.5541 | 1500 | 2.4375 | 101.6211 | 100.4407 | |
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| 0.0593 | 12.7389 | 2000 | 2.5851 | 108.4180 | 107.2811 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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