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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_15_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-300m-br |
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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: common_voice_15_0 |
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type: common_voice_15_0 |
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config: br |
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split: None |
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args: br |
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metrics: |
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- name: Wer |
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type: wer |
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value: 49.79811574697174 |
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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-300m-br |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the common_voice_15_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8887 |
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- Wer: 49.7981 |
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- Cer: 17.3877 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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: 16 |
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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: 40 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 5.1153 | 2.18 | 1000 | 2.8854 | 100.0 | 100.0 | |
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| 1.4117 | 4.36 | 2000 | 0.9161 | 71.2786 | 25.3180 | |
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| 0.7888 | 6.54 | 3000 | 0.7753 | 62.7456 | 22.0767 | |
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| 0.6316 | 8.71 | 4000 | 0.7550 | 58.1786 | 20.5383 | |
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| 0.5434 | 10.89 | 5000 | 0.7508 | 56.5096 | 20.1168 | |
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| 0.4672 | 13.07 | 6000 | 0.7844 | 54.9125 | 19.3835 | |
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| 0.4237 | 15.25 | 7000 | 0.7786 | 53.2705 | 18.5765 | |
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| 0.3899 | 17.43 | 8000 | 0.8050 | 53.0552 | 18.6105 | |
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| 0.3607 | 19.61 | 9000 | 0.8280 | 51.9874 | 18.3024 | |
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| 0.3355 | 21.79 | 10000 | 0.7967 | 51.5388 | 17.9811 | |
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| 0.3098 | 23.97 | 11000 | 0.8296 | 51.2876 | 17.9547 | |
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| 0.2937 | 26.14 | 12000 | 0.8544 | 50.9915 | 17.7827 | |
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| 0.2793 | 28.32 | 13000 | 0.8909 | 51.5478 | 18.1286 | |
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| 0.2641 | 30.5 | 14000 | 0.8740 | 50.4800 | 17.6561 | |
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| 0.2552 | 32.68 | 15000 | 0.8832 | 49.9776 | 17.4463 | |
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| 0.2467 | 34.86 | 16000 | 0.8753 | 50.3096 | 17.4765 | |
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| 0.2378 | 37.04 | 17000 | 0.8895 | 49.8789 | 17.3952 | |
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| 0.2337 | 39.22 | 18000 | 0.8887 | 49.7981 | 17.3877 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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