---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-korean-all
  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-large-xls-r-korean-all

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: 0.1535
- Cer: 0.0329

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0206        | 0.36  | 500   | 3.3589          | 0.9871 |
| 0.6381        | 0.72  | 1000  | 0.6371          | 0.1714 |
| 0.3951        | 1.08  | 1500  | 0.4320          | 0.125  |
| 0.2858        | 1.44  | 2000  | 0.3546          | 0.1056 |
| 0.2545        | 1.8   | 2500  | 0.2925          | 0.0872 |
| 0.1833        | 2.16  | 3000  | 0.2520          | 0.0743 |
| 0.1898        | 2.51  | 3500  | 0.2386          | 0.0679 |
| 0.1981        | 2.87  | 4000  | 0.2135          | 0.0631 |
| 0.123         | 3.23  | 4500  | 0.2129          | 0.0576 |
| 0.1221        | 3.59  | 5000  | 0.2013          | 0.0543 |
| 0.1218        | 3.95  | 5500  | 0.2000          | 0.0554 |
| 0.1096        | 4.31  | 6000  | 0.1884          | 0.0507 |
| 0.1113        | 4.67  | 6500  | 0.1781          | 0.0455 |
| 0.075         | 5.03  | 7000  | 0.1811          | 0.0458 |
| 0.0922        | 5.39  | 7500  | 0.1748          | 0.0455 |
| 0.0766        | 5.75  | 8000  | 0.1807          | 0.0434 |
| 0.0811        | 6.11  | 8500  | 0.1699          | 0.0411 |
| 0.0876        | 6.47  | 9000  | 0.1641          | 0.0398 |
| 0.0913        | 6.82  | 9500  | 0.1632          | 0.0392 |
| 0.0658        | 7.18  | 10000 | 0.1667          | 0.0388 |
| 0.0831        | 7.54  | 10500 | 0.1613          | 0.0375 |
| 0.0716        | 7.9   | 11000 | 0.1552          | 0.0361 |
| 0.0485        | 8.26  | 11500 | 0.1534          | 0.0351 |
| 0.0469        | 8.62  | 12000 | 0.1541          | 0.0343 |
| 0.0503        | 8.98  | 12500 | 0.1497          | 0.0340 |
| 0.041         | 9.34  | 13000 | 0.1535          | 0.0337 |
| 0.0556        | 9.7   | 13500 | 0.1535          | 0.0329 |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.12.1+cu113
- Datasets 2.14.5
- Tokenizers 0.13.3