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--- |
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library_name: transformers |
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language: |
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- wo |
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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-WOLOF-5-hours-Google-Fleurs-dataset |
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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 |
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type: google/fleurs |
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config: wo_sn |
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split: None |
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args: 'config: wo, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 49.03357070193286 |
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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/asr-africa-research-team/ASR%20Africa/runs/79l4ms4x) |
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# Whisper-WOLOF-5-hours-Google-Fleurs-dataset |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5579 |
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- Wer: 49.0336 |
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- Cer: 18.1546 |
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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: 32 |
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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: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 50 |
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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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| 0.7747 | 12.1951 | 500 | 1.3158 | 48.9318 | 18.0097 | |
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| 0.0052 | 24.3902 | 1000 | 1.4793 | 48.9431 | 18.1792 | |
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| 0.0012 | 36.5854 | 1500 | 1.5371 | 49.2144 | 18.0521 | |
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| 0.0008 | 48.7805 | 2000 | 1.5579 | 49.0336 | 18.1546 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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