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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-large-v3 |
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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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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Large-V3 Portuguese |
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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-foundation/common_voice_13_0 pt |
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type: mozilla-foundation/common_voice_13_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: 5.180231985016266 |
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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 Large-V3 Portuguese |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the mozilla-foundation/common_voice_13_0 pt dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3553 |
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- Wer: 5.1802 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 20000 |
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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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| 0.0316 | 3.53 | 1000 | 0.1632 | 4.6397 | |
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| 0.0066 | 7.05 | 2000 | 0.2164 | 4.8944 | |
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| 0.0032 | 10.58 | 3000 | 0.2438 | 5.0619 | |
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| 0.0011 | 14.11 | 4000 | 0.2523 | 5.0751 | |
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| 0.0037 | 17.64 | 5000 | 0.2481 | 5.2460 | |
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| 0.0011 | 21.16 | 6000 | 0.2683 | 5.3692 | |
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| 0.0033 | 24.69 | 7000 | 0.2756 | 5.5844 | |
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| 0.0009 | 28.22 | 8000 | 0.2769 | 5.4628 | |
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| 0.0013 | 31.75 | 9000 | 0.2664 | 5.4349 | |
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| 0.0007 | 35.27 | 10000 | 0.3020 | 5.4776 | |
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| 0.0005 | 38.8 | 11000 | 0.2886 | 5.4595 | |
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| 0.0003 | 42.33 | 12000 | 0.3016 | 5.3265 | |
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| 0.0003 | 45.86 | 13000 | 0.3040 | 5.5121 | |
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| 0.0001 | 49.38 | 14000 | 0.3147 | 5.4480 | |
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| 0.0001 | 52.91 | 15000 | 0.3071 | 5.4300 | |
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| 0.0 | 56.44 | 16000 | 0.3307 | 5.3051 | |
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| 0.0 | 59.96 | 17000 | 0.3412 | 5.2476 | |
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| 0.0 | 63.49 | 18000 | 0.3483 | 5.2016 | |
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| 0.0 | 67.02 | 19000 | 0.3532 | 5.1884 | |
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| 0.0 | 70.55 | 20000 | 0.3553 | 5.1802 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.15.1 |
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