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--- |
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language: |
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- sw |
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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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- mozilla-foundation/common_voice_15_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Incremental Swahili Luganda |
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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: Mix data |
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type: mozilla-foundation/common_voice_15_0 |
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config: lg |
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split: validation |
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args: 'config: lu, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 31.718294383636902 |
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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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# Incremental Swahili Luganda |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Mix data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3430 |
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- Wer: 31.7183 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 500 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 0.2355 | 0.0894 | 500 | 0.3831 | 35.9432 | |
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| 0.2275 | 0.1789 | 1000 | 0.3818 | 35.3379 | |
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| 0.245 | 0.2683 | 1500 | 0.3727 | 34.4346 | |
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| 0.2321 | 0.3577 | 2000 | 0.3637 | 33.5439 | |
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| 0.2396 | 0.4472 | 2500 | 0.3569 | 32.9164 | |
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| 0.2231 | 0.5366 | 3000 | 0.3512 | 33.0780 | |
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| 0.2039 | 0.6261 | 3500 | 0.3468 | 32.3184 | |
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| 0.2283 | 0.7155 | 4000 | 0.3430 | 31.7183 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.2+cu118 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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