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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: 4.600269444353169 |
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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: 0.4315 |
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- Wer: 4.6003 |
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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-06 |
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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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| 0.0702 | 3.53 | 1000 | 0.1289 | 4.0367 | |
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| 0.0247 | 7.05 | 2000 | 0.1806 | 4.4294 | |
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| 0.0074 | 10.58 | 3000 | 0.2821 | 4.7481 | |
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| 0.0022 | 14.11 | 4000 | 0.3160 | 4.6249 | |
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| 0.0016 | 17.64 | 5000 | 0.3261 | 4.6479 | |
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| 0.0027 | 21.16 | 6000 | 0.3373 | 4.6479 | |
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| 0.0009 | 24.69 | 7000 | 0.3642 | 4.7087 | |
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| 0.0007 | 28.22 | 8000 | 0.3551 | 4.6611 | |
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| 0.0006 | 31.75 | 9000 | 0.3741 | 4.7481 | |
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| 0.0004 | 35.27 | 10000 | 0.3755 | 4.6791 | |
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| 0.0008 | 38.8 | 11000 | 0.3690 | 4.6381 | |
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| 0.0002 | 42.33 | 12000 | 0.3888 | 4.5115 | |
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| 0.0002 | 45.86 | 13000 | 0.3982 | 4.5855 | |
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| 0.0001 | 49.38 | 14000 | 0.4040 | 4.6085 | |
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| 0.0001 | 52.91 | 15000 | 0.4100 | 4.5888 | |
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| 0.0001 | 56.44 | 16000 | 0.4165 | 4.5871 | |
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| 0.0001 | 59.96 | 17000 | 0.4211 | 4.5855 | |
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| 0.0001 | 63.49 | 18000 | 0.4265 | 4.5838 | |
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| 0.0001 | 67.02 | 19000 | 0.4302 | 4.5921 | |
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| 0.0001 | 70.55 | 20000 | 0.4315 | 4.6003 | |
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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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