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  2. model.safetensors +1 -1
README.md CHANGED
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  ---
 
 
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  license: apache-2.0
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- base_model: DereAbdulhameed/whisper-cli-yor
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  tags:
 
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  - generated_from_trainer
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  datasets:
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- - common_voice_16_1
 
 
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  model-index:
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- - name: new_whisper_yoruba
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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- # new_whisper_yoruba
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- This model is a fine-tuned version of [DereAbdulhameed/whisper-cli-yor](https://huggingface.co/DereAbdulhameed/whisper-cli-yor) on the common_voice_16_1 dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 1.3864
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- - eval_wer: 34.4790
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- - eval_runtime: 460.5039
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- - eval_samples_per_second: 3.748
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- - eval_steps_per_second: 0.469
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- - epoch: 17.01
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- - step: 1000
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  ## Model description
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@@ -52,6 +65,16 @@ The following hyperparameters were used during training:
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  - training_steps: 4000
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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  - Transformers 4.40.0.dev0
 
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  ---
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+ language:
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+ - yo
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  license: apache-2.0
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+ base_model: DereAbdulhameed/new_whisper_yoruba
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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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+ - OpenSLR
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+ metrics:
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+ - wer
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  model-index:
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+ - name: Whisper Small Yoruba - Dere Abdulhameed
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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 16.1 & SLR86
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+ type: OpenSLR
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+ config: yo
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+ split: None
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+ args: yo
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 33.08135740700457
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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 Yoruba - Dere Abdulhameed
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+ This model is a fine-tuned version of [DereAbdulhameed/new_whisper_yoruba](https://huggingface.co/DereAbdulhameed/new_whisper_yoruba) on the Common Voice 16.1 & SLR86 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7726
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+ - Wer: 33.0814
 
 
 
 
 
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  ## Model description
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  - training_steps: 4000
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  - mixed_precision_training: Native AMP
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.0001 | 17.01 | 1000 | 1.6166 | 33.3043 |
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+ | 0.0001 | 35.01 | 2000 | 1.7029 | 32.9563 |
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+ | 0.0 | 53.01 | 3000 | 1.7515 | 33.0868 |
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+ | 0.0 | 71.01 | 4000 | 1.7726 | 33.0814 |
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+
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+
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  ### Framework versions
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  - Transformers 4.40.0.dev0
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