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README.md
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---
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language:
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- af
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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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- voice-biomarkers/openslr-32-hq-SA-languages-Afrikaans
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper Tiny af
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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: voice-biomarkers/openslr-32-hq-SA-languages-Afrikaans
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config: af_za
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split: test
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args: af_za
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metrics:
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- name: Wer
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type: wer
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value: 48.72727272727273
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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 af
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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 17.0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6355
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- Wer: 48.7273
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- Cer: 19.0658
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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: 128
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- eval_batch_size: 128
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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_ratio: 0.04
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- training_steps: 5000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
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| 0.0133 | 14.0068 | 1000 | 1.3968 | 48.6926 | 20.3824 |
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| 0.0032 | 28.0136 | 2000 | 1.5069 | 48.6234 | 19.1039 |
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| 0.0016 | 43.0066 | 3000 | 1.5777 | 48.6926 | 19.0775 |
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| 0.0011 | 57.0134 | 4000 | 1.6203 | 48.4675 | 19.1273 |
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| 0.0009 | 72.0064 | 5000 | 1.6355 | 48.7273 | 19.0658 |
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### Framework versions
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- Transformers 4.42.0.dev0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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