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--- |
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license: apache-2.0 |
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base_model: jonatasgrosman/wav2vec2-xls-r-1b-portuguese |
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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: wav2vec2-xls-r-1b-portuguese-casa-civil-030124 |
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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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# wav2vec2-xls-r-1b-portuguese-casa-civil-030124 |
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-xls-r-1b-portuguese](https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-portuguese) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5479 |
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- Wer: 0.1310 |
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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: 0.0003 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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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- num_epochs: 30 |
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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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| 28.5913 | 2.0 | 100 | 1.2903 | 0.1460 | |
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| 1.1869 | 4.0 | 200 | 0.6083 | 0.1537 | |
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| 0.8173 | 6.0 | 300 | 0.7054 | 0.2217 | |
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| 0.7882 | 8.0 | 400 | 0.7377 | 0.2711 | |
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| 0.6783 | 10.0 | 500 | 0.7785 | 0.2321 | |
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| 0.5541 | 12.0 | 600 | 0.6881 | 0.2394 | |
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| 0.5104 | 14.0 | 700 | 0.7285 | 0.2270 | |
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| 0.344 | 16.0 | 800 | 0.6114 | 0.1991 | |
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| 0.304 | 18.0 | 900 | 0.5559 | 0.1906 | |
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| 0.2315 | 20.0 | 1000 | 0.6833 | 0.1727 | |
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| 0.2144 | 22.0 | 1100 | 0.5632 | 0.1695 | |
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| 0.1725 | 24.0 | 1200 | 0.5597 | 0.1463 | |
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| 0.1492 | 26.0 | 1300 | 0.5356 | 0.1472 | |
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| 0.118 | 28.0 | 1400 | 0.5499 | 0.1344 | |
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| 0.1083 | 30.0 | 1500 | 0.5479 | 0.1310 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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