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--- |
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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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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-base-google-fleurs-pt-br |
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results: [] |
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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-google-fleurs-pt-br |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6283 |
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- Wer: 25.9071 |
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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: 2.5e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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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: 120 |
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- training_steps: 2400 |
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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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| 0.0871 | 2.72 | 400 | 0.4838 | 24.4078 | |
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| 0.0066 | 5.44 | 800 | 0.5647 | 25.5452 | |
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| 0.0013 | 8.16 | 1200 | 0.5981 | 25.6110 | |
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| 0.0008 | 10.88 | 1600 | 0.6143 | 25.6533 | |
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| 0.0006 | 13.61 | 2000 | 0.6245 | 25.7661 | |
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| 0.0006 | 16.33 | 2400 | 0.6283 | 25.9071 | |
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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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