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--- |
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language: |
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- nyn |
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license: apache-2.0 |
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base_model: openai/whisper-base.en |
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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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- tericlabs |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper base 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: Sunbird |
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type: tericlabs |
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metrics: |
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- name: Wer |
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type: wer |
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value: 40.80100125156446 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ai-research-lab/huggingface/runs/p2aegccn) |
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# Whisper base Luganda |
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This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the Sunbird dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6134 |
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- Wer: 40.8010 |
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- Cer: 10.6921 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 1000 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:| |
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| 0.3459 | 6.3694 | 1000 | 0.5885 | 45.1815 | 14.4972 | |
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| 0.0532 | 12.7389 | 2000 | 0.5441 | 38.6733 | 10.0723 | |
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| 0.0108 | 19.1083 | 3000 | 0.6118 | 39.9249 | 10.2789 | |
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| 0.0044 | 25.4777 | 4000 | 0.6134 | 40.8010 | 10.6921 | |
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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 2.19.2 |
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- Tokenizers 0.19.1 |
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