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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: 30.713561255969235 |
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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: 0.3391 |
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- Wer: 30.7136 |
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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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| 0.1672 | 0.0998 | 500 | 0.3706 | 33.9074 | |
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| 0.172 | 0.1996 | 1000 | 0.3714 | 33.9803 | |
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| 0.2094 | 0.2995 | 1500 | 0.3640 | 33.2407 | |
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| 0.1927 | 0.3993 | 2000 | 0.3577 | 32.5233 | |
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| 0.1905 | 0.4991 | 2500 | 0.3521 | 31.8810 | |
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| 0.1735 | 0.5989 | 3000 | 0.3470 | 31.3189 | |
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| 0.157 | 0.6987 | 3500 | 0.3428 | 31.0052 | |
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| 0.1784 | 0.7986 | 4000 | 0.3391 | 30.7136 | |
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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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