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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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model-index:
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- name: wav2vec2-xls-r-300m_phoneme-mfa_korean_samsung-54k_003
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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-xls-r-300m_phoneme-mfa_korean_samsung-54k_003
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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 None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2517
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- Per: 0.0763
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- Learning Rate: 0.0001
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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: 0.0001
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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_ratio: 0.2
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- num_epochs: 20
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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 | Per | Rate |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
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| 5.1523 | 1.0 | 3362 | 0.6130 | 0.1649 | 0.0000 |
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| 0.512 | 2.0 | 6724 | 0.2874 | 0.0959 | 0.0000 |
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| 0.3554 | 3.0 | 10086 | 0.2540 | 0.0868 | 0.0001 |
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| 0.2992 | 4.0 | 13448 | 0.2578 | 0.0749 | 0.0001 |
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| 0.2619 | 5.0 | 16810 | 0.2524 | 0.0808 | 0.0001 |
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| 0.2313 | 6.0 | 20172 | 0.2496 | 0.0738 | 0.0001 |
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| 0.2084 | 7.0 | 23534 | 0.2420 | 0.0523 | 0.0001 |
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| 0.1928 | 8.0 | 26896 | 0.2425 | 0.0523 | 0.0001 |
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| 0.1791 | 9.0 | 30258 | 0.2426 | 0.0748 | 0.0001 |
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| 0.1678 | 10.0 | 33620 | 0.2427 | 0.0752 | 0.0001 |
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| 0.1584 | 11.0 | 36982 | 0.2526 | 0.0792 | 0.0001 |
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| 0.1483 | 12.0 | 40344 | 0.2517 | 0.0763 | 0.0001 |
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### Framework versions
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- Transformers 4.21.3
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- Pytorch 1.12.1
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- Datasets 2.4.0
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- Tokenizers 0.12.1
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