---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
metrics:
- wer
model-index:
- name: ko-xlsr2
  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. -->

# ko-xlsr2

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4239
- Cer: 0.1113
- Wer: 0.3038

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.7721        | 0.94  | 2000  | 1.1368          | 0.2903 | 0.6589 |
| 1.3501        | 1.89  | 4000  | 0.8561          | 0.2240 | 0.5451 |
| 1.2133        | 2.83  | 6000  | 0.7505          | 0.2003 | 0.4974 |
| 1.0981        | 3.77  | 8000  | 0.6768          | 0.1842 | 0.4686 |
| 1.0375        | 4.72  | 10000 | 0.6413          | 0.1707 | 0.4404 |
| 0.9927        | 5.66  | 12000 | 0.6106          | 0.1634 | 0.4246 |
| 0.9439        | 6.6   | 14000 | 0.5999          | 0.1613 | 0.4159 |
| 0.9059        | 7.55  | 16000 | 0.5740          | 0.1535 | 0.3985 |
| 0.8772        | 8.49  | 18000 | 0.5569          | 0.1478 | 0.3954 |
| 0.8483        | 9.43  | 20000 | 0.5407          | 0.1427 | 0.3784 |
| 0.81          | 10.37 | 22000 | 0.5283          | 0.1415 | 0.3744 |
| 0.793         | 11.32 | 24000 | 0.5179          | 0.1366 | 0.3663 |
| 0.7577        | 12.26 | 26000 | 0.5059          | 0.1359 | 0.3595 |
| 0.7379        | 13.2  | 28000 | 0.4969          | 0.1333 | 0.3532 |
| 0.7328        | 14.15 | 30000 | 0.4908          | 0.1308 | 0.3475 |
| 0.7119        | 15.09 | 32000 | 0.4887          | 0.1286 | 0.3478 |
| 0.7572        | 16.03 | 34000 | 0.5170          | 0.1327 | 0.3577 |
| 0.8198        | 16.98 | 36000 | 0.5839          | 0.1432 | 0.3825 |
| 0.8008        | 17.92 | 38000 | 0.5447          | 0.1376 | 0.3661 |
| 0.759         | 18.86 | 40000 | 0.4998          | 0.1337 | 0.3534 |
| 0.6907        | 19.81 | 42000 | 0.4710          | 0.1288 | 0.3412 |
| 0.659         | 20.75 | 44000 | 0.4578          | 0.1242 | 0.3325 |
| 0.6345        | 21.69 | 46000 | 0.4531          | 0.1221 | 0.3257 |
| 0.6242        | 22.64 | 48000 | 0.4498          | 0.1209 | 0.3218 |
| 0.6163        | 23.58 | 50000 | 0.4552          | 0.1194 | 0.3188 |
| 0.6121        | 24.52 | 52000 | 0.4633          | 0.1154 | 0.3137 |
| 0.6054        | 25.47 | 54000 | 0.4623          | 0.1176 | 0.3171 |
| 0.591         | 26.41 | 56000 | 0.4413          | 0.1146 | 0.3116 |
| 0.5713        | 27.35 | 58000 | 0.4338          | 0.1135 | 0.3093 |
| 0.5703        | 28.3  | 60000 | 0.4280          | 0.1121 | 0.3061 |
| 0.5576        | 29.24 | 62000 | 0.4248          | 0.1119 | 0.3047 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1