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--- |
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language: |
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- ig |
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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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- generated_from_trainer |
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datasets: |
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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 Small Igbo |
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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: google/fleurs-jboat |
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type: google/fleurs |
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config: ig_ng |
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split: test |
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args: ig_ng |
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metrics: |
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- name: Wer |
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type: wer |
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value: 44.01272438082254 |
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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 Igbo |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs-jboat dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0619 |
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- Wer Ortho: 47.8937 |
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- Wer: 44.0127 |
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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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- training_steps: 4000 |
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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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| 0.3161 | 2.6455 | 500 | 0.7413 | 50.2340 | 46.1448 | |
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| 0.0421 | 5.2910 | 1000 | 0.8582 | 49.0269 | 44.8004 | |
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| 0.0168 | 7.9365 | 1500 | 0.9246 | 47.6351 | 43.5204 | |
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| 0.0075 | 10.5820 | 2000 | 0.9912 | 47.7541 | 43.3121 | |
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| 0.0051 | 13.2275 | 2500 | 1.0277 | 47.7377 | 43.3954 | |
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| 0.0067 | 15.8730 | 3000 | 1.0354 | 47.6638 | 43.1644 | |
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| 0.0041 | 18.5185 | 3500 | 1.0722 | 48.3864 | 44.1112 | |
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| 0.0028 | 21.1640 | 4000 | 1.0619 | 47.8937 | 44.0127 | |
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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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