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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- fleurs |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-kr-jw4169 |
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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: fleurs |
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type: fleurs |
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config: ko_kr |
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split: train |
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args: ko_kr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.519593179778642 |
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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-xls-r-300m-kr-jw4169 |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9752 |
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- Wer: 0.5196 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 35.084 | 1.39 | 200 | 6.8536 | 1.0 | |
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| 4.853 | 2.78 | 400 | 4.6246 | 1.0 | |
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| 4.5491 | 4.17 | 600 | 4.3815 | 1.0 | |
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| 2.799 | 5.55 | 800 | 1.7402 | 0.8642 | |
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| 1.3872 | 6.94 | 1000 | 1.2019 | 0.7448 | |
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| 0.9599 | 8.33 | 1200 | 1.0594 | 0.7134 | |
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| 0.675 | 9.72 | 1400 | 0.9321 | 0.6404 | |
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| 0.4775 | 11.11 | 1600 | 0.9088 | 0.5911 | |
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| 0.3479 | 12.5 | 1800 | 0.9430 | 0.6010 | |
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| 0.2712 | 13.89 | 2000 | 0.8948 | 0.5854 | |
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| 0.2283 | 15.28 | 2200 | 0.9009 | 0.5495 | |
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| 0.1825 | 16.67 | 2400 | 0.9079 | 0.5501 | |
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| 0.161 | 18.06 | 2600 | 0.9518 | 0.5390 | |
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| 0.1394 | 19.44 | 2800 | 0.9529 | 0.5399 | |
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| 0.1266 | 20.83 | 3000 | 0.9505 | 0.5283 | |
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| 0.1102 | 22.22 | 3200 | 0.9748 | 0.5328 | |
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| 0.101 | 23.61 | 3400 | 0.9593 | 0.5316 | |
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| 0.0907 | 25.0 | 3600 | 0.9832 | 0.5292 | |
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| 0.0833 | 26.39 | 3800 | 0.9773 | 0.5181 | |
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| 0.0781 | 27.78 | 4000 | 0.9736 | 0.5163 | |
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| 0.0744 | 29.17 | 4200 | 0.9752 | 0.5196 | |
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### Framework versions |
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- Transformers 4.25.0.dev0 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 2.6.1 |
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- Tokenizers 0.13.1 |
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