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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-small |
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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 small 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: 17.33354880413704 |
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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 small using Common Voice 16 (pt) |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) 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: 0.2712 |
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- Wer: 17.3335 |
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- Wer Normalized: 11.3321 |
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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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- 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: 5000 |
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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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| 0.2591 | 0.37 | 500 | 0.2776 | 20.0727 | 13.6707 | |
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| 0.2626 | 0.74 | 1000 | 0.2599 | 19.4005 | 13.3337 | |
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| 0.1131 | 1.11 | 1500 | 0.2516 | 18.0414 | 12.1330 | |
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| 0.1016 | 1.48 | 2000 | 0.2482 | 18.3597 | 11.9244 | |
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| 0.1094 | 1.85 | 2500 | 0.2411 | 17.4192 | 11.6017 | |
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| 0.0524 | 2.22 | 3000 | 0.2512 | 17.3546 | 11.4637 | |
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| 0.0433 | 2.59 | 3500 | 0.2496 | 17.0895 | 11.2984 | |
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| 0.0453 | 2.96 | 4000 | 0.2479 | 17.0362 | 11.2679 | |
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| 0.0201 | 3.33 | 4500 | 0.2693 | 17.6632 | 11.7109 | |
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| 0.0229 | 3.7 | 5000 | 0.2712 | 17.3335 | 11.3321 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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