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--- |
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library_name: transformers |
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language: |
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- gn |
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license: apache-2.0 |
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base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Common Voice 16 |
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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 16 |
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type: mozilla-foundation/common_voice_16_1 |
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config: gn |
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split: None |
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args: gn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 39.84010659560293 |
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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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# Common Voice 16 |
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This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2438 |
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- Wer: 39.8401 |
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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: 16 |
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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: constant_with_warmup |
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- lr_scheduler_warmup_steps: 3000 |
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- training_steps: 3000 |
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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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| 1.2579 | 0.4955 | 500 | 0.3710 | 53.4310 | |
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| 0.919 | 0.9911 | 1000 | 0.3295 | 49.9001 | |
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| 0.746 | 1.4866 | 1500 | 0.2902 | 45.1033 | |
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| 0.6767 | 1.9822 | 2000 | 0.2674 | 43.3711 | |
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| 0.574 | 2.4777 | 2500 | 0.2677 | 42.5716 | |
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| 0.5485 | 2.9732 | 3000 | 0.2438 | 39.8401 | |
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### Framework versions |
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- Transformers 4.44.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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