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README.md
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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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