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--- |
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language: |
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- pt |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base using Common Voice 16 (pt) |
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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: Mozilla Common Voices - 16.0 - Portuguese |
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type: mozilla-foundation/common_voice_16_0 |
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config: pt |
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split: test |
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args: pt |
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metrics: |
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- name: Wer |
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type: wer |
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value: 26.192630898513254 |
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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 Base using Common Voice 16 (pt) |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Mozilla Common Voices - 16.0 - Portuguese dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4574 |
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- Wer: 26.1926 |
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- Wer Normalized: 20.0029 |
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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: 2e-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_steps: 500 |
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- training_steps: 7000 |
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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 | Wer Normalized | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------:| |
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| 0.4883 | 0.74 | 1000 | 0.3803 | 28.0317 | 21.8327 | |
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| 0.2659 | 1.48 | 2000 | 0.3677 | 26.3688 | 20.1666 | |
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| 0.1251 | 2.22 | 3000 | 0.3730 | 26.3752 | 20.4620 | |
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| 0.1071 | 2.96 | 4000 | 0.3867 | 25.5026 | 19.5470 | |
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| 0.0523 | 3.7 | 5000 | 0.4148 | 25.7094 | 19.6851 | |
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| 0.02 | 4.44 | 6000 | 0.4491 | 25.6803 | 19.5759 | |
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| 0.0134 | 5.18 | 7000 | 0.4574 | 26.1926 | 20.0029 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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