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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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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-large-xlsr-53-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: 54.71511888739345 |
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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-large-xlsr-53-br |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) 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: 0.7879 |
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- Wer: 54.7151 |
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- Cer: 19.2493 |
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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: 6e-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: 4 |
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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: 300 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
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| 6.3257 | 2.18 | 500 | 3.0700 | 100.0 | 99.0871 | |
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| 2.2071 | 4.36 | 1000 | 1.1541 | 80.0449 | 29.4230 | |
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| 1.0019 | 6.54 | 1500 | 0.8986 | 69.2059 | 24.3938 | |
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| 0.7796 | 8.71 | 2000 | 0.8015 | 63.3737 | 22.1296 | |
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| 0.6677 | 10.89 | 2500 | 0.8014 | 61.4984 | 21.4568 | |
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| 0.5937 | 13.07 | 3000 | 0.7623 | 58.9323 | 20.4929 | |
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| 0.5454 | 15.25 | 3500 | 0.7975 | 57.8466 | 20.2585 | |
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| 0.5075 | 17.43 | 4000 | 0.7831 | 56.7250 | 19.7879 | |
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| 0.4837 | 19.61 | 4500 | 0.7902 | 55.9623 | 19.5101 | |
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| 0.4529 | 21.79 | 5000 | 0.7851 | 54.9753 | 19.0924 | |
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| 0.4381 | 23.97 | 5500 | 0.7865 | 55.1727 | 19.3211 | |
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| 0.4208 | 26.14 | 6000 | 0.8168 | 55.1817 | 19.3967 | |
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| 0.4197 | 28.32 | 6500 | 0.7879 | 54.7151 | 19.2493 | |
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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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