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README.md
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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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- zeroth_korean
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metrics:
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- wer
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model-index:
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- name: output
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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: zeroth_korean
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type: zeroth_korean
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config: clean
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split: train
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args: clean
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metrics:
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- name: Wer
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type: wer
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value: 0.988221081244337
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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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# output
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This model was trained from scratch on the zeroth_korean dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3624
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- Wer: 0.9882
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- Cer: 0.5429
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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: 7.5e-05
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- train_batch_size: 16
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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: 64
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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: 2000
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- num_epochs: 10.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 19.558 | 1.44 | 500 | 19.4094 | 1.0 | 1.0 |
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| 4.7968 | 2.87 | 1000 | 4.7828 | 1.0 | 1.0 |
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| 4.5125 | 4.31 | 1500 | 4.4959 | 0.9991 | 0.9540 |
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| 4.2202 | 5.75 | 2000 | 4.2905 | 0.9923 | 0.8520 |
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| 3.7774 | 7.18 | 2500 | 3.2846 | 1.0356 | 0.6652 |
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| 3.1418 | 8.62 | 3000 | 2.3624 | 0.9882 | 0.5429 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.13.1
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- Datasets 2.6.1
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- Tokenizers 0.11.0
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