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--- |
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base_model: cpierse/wav2vec2-large-xlsr-53-esperanto |
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datasets: |
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- audiofolder |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: TrainEsperanto |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: audiofolder |
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type: audiofolder |
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config: default |
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split: None |
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args: default |
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metrics: |
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- type: wer |
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value: 0.1883670612192949 |
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name: Wer |
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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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# TrainEsperanto |
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This model is a fine-tuned version of [cpierse/wav2vec2-large-xlsr-53-esperanto](https://huggingface.co/cpierse/wav2vec2-large-xlsr-53-esperanto) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0591 |
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- Wer: 0.1884 |
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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: 32 |
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- eval_batch_size: 8 |
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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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- num_epochs: 30 |
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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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| 5.9902 | 2.6596 | 500 | 8.6294 | 1.0309 | |
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| 3.3 | 5.3191 | 1000 | 2.9688 | 1.0 | |
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| 2.8744 | 7.9787 | 1500 | 2.4117 | 1.0 | |
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| 0.7214 | 10.6383 | 2000 | 0.1825 | 0.2954 | |
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| 0.1552 | 13.2979 | 2500 | 0.0689 | 0.1971 | |
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| 0.1038 | 15.9574 | 3000 | 0.0621 | 0.1932 | |
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| 0.092 | 18.6170 | 3500 | 0.0624 | 0.1900 | |
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| 0.0877 | 21.2766 | 4000 | 0.0615 | 0.1926 | |
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| 0.082 | 23.9362 | 4500 | 0.0609 | 0.1899 | |
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| 0.0779 | 26.5957 | 5000 | 0.0591 | 0.1887 | |
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| 0.077 | 29.2553 | 5500 | 0.0591 | 0.1884 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1 |
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- Datasets 2.19.1 |
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- Tokenizers 0.20.1 |
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