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README.md
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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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