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--- |
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language: |
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- nyn |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- tericlabs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Runyankore |
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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: Yogera data |
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type: tericlabs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 47.48073503260225 |
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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 Runyankore |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yogera data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6975 |
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- Wer: 47.4807 |
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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: 8 |
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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: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 1000 |
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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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| 3.7277 | 0.43 | 100 | 2.6880 | 98.2810 | |
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| 2.265 | 0.85 | 200 | 1.8155 | 84.8251 | |
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| 1.6872 | 1.28 | 300 | 1.3734 | 75.1630 | |
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| 1.25 | 1.7 | 400 | 0.9704 | 65.2638 | |
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| 0.9047 | 2.13 | 500 | 0.8496 | 57.9727 | |
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| 0.7852 | 2.55 | 600 | 0.7705 | 57.0836 | |
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| 0.7065 | 2.98 | 700 | 0.7080 | 51.4523 | |
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| 0.4952 | 3.4 | 800 | 0.6939 | 50.3853 | |
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| 0.516 | 3.83 | 900 | 0.6786 | 49.0219 | |
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| 0.4005 | 4.26 | 1000 | 0.6975 | 47.4807 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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