---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-xls-r-300m_phoneme-mfa_korean_samsung-54k_003
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-xls-r-300m_phoneme-mfa_korean_samsung-54k_003

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.
It achieves the following results on the evaluation set:
- Loss: 0.2517
- Per: 0.0763
- Learning Rate: 0.0001

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 20 (EarlyStopping: patience -5)
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | PER    | Rate   |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 5.1523        | 1.0   | 3362  | 0.6130          | 0.1649 | 0.0000 |
| 0.512         | 2.0   | 6724  | 0.2874          | 0.0959 | 0.0000 |
| 0.3554        | 3.0   | 10086 | 0.2540          | 0.0868 | 0.0001 |
| 0.2992        | 4.0   | 13448 | 0.2578          | 0.0749 | 0.0001 |
| 0.2619        | 5.0   | 16810 | 0.2524          | 0.0808 | 0.0001 |
| 0.2313        | 6.0   | 20172 | 0.2496          | 0.0738 | 0.0001 |
| 0.2084        | 7.0   | 23534 | 0.2420          | 0.0523 | 0.0001 |
| 0.1928        | 8.0   | 26896 | 0.2425          | 0.0523 | 0.0001 |
| 0.1791        | 9.0   | 30258 | 0.2426          | 0.0748 | 0.0001 |
| 0.1678        | 10.0  | 33620 | 0.2427          | 0.0752 | 0.0001 |
| 0.1584        | 11.0  | 36982 | 0.2526          | 0.0792 | 0.0001 |
| 0.1483        | 12.0  | 40344 | 0.2517          | 0.0763 | 0.0001 |

Final Result: PER 3.88%

### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1