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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: xls-r-fleurs_nl-run4 |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.46057420137484834 |
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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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# xls-r-fleurs_nl-run4 |
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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 FLEURS (nl) dataset. |
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It achieves the following results: |
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- Wer (Validation): 42.94% |
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- Wer (Test): 43.74% |
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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: 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: 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 (Train) | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 0.1216 | 1.55 | 100 | 0.5803 | 0.4294 | |
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| 0.0775 | 3.1 | 200 | 0.6325 | 0.4420 | |
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| 0.0705 | 4.65 | 300 | 0.6473 | 0.4606 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
