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--- |
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language: |
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- nl |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-common_voice-nl-demo |
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results: [] |
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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-common_voice-nl-demo |
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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 - NL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3523 |
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- Wer: 0.2046 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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: 500 |
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- num_epochs: 15.0 |
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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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| 3.0536 | 1.12 | 500 | 0.5349 | 0.4338 | |
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| 0.2543 | 2.24 | 1000 | 0.3859 | 0.3029 | |
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| 0.1472 | 3.36 | 1500 | 0.3471 | 0.2818 | |
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| 0.1088 | 4.47 | 2000 | 0.3489 | 0.2731 | |
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| 0.0855 | 5.59 | 2500 | 0.3582 | 0.2558 | |
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| 0.0721 | 6.71 | 3000 | 0.3457 | 0.2471 | |
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| 0.0653 | 7.83 | 3500 | 0.3299 | 0.2357 | |
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| 0.0527 | 8.95 | 4000 | 0.3440 | 0.2334 | |
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| 0.0444 | 10.07 | 4500 | 0.3417 | 0.2289 | |
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| 0.0404 | 11.19 | 5000 | 0.3691 | 0.2204 | |
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| 0.0345 | 12.3 | 5500 | 0.3453 | 0.2102 | |
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| 0.0288 | 13.42 | 6000 | 0.3634 | 0.2089 | |
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| 0.027 | 14.54 | 6500 | 0.3532 | 0.2044 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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