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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-kr-jw4169
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: ko_kr
split: train
args: ko_kr
metrics:
- name: Wer
type: wer
value: 0.519593179778642
---
<!-- 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-300m-kr-jw4169
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9752
- Wer: 0.5196
## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 35.084 | 1.39 | 200 | 6.8536 | 1.0 |
| 4.853 | 2.78 | 400 | 4.6246 | 1.0 |
| 4.5491 | 4.17 | 600 | 4.3815 | 1.0 |
| 2.799 | 5.55 | 800 | 1.7402 | 0.8642 |
| 1.3872 | 6.94 | 1000 | 1.2019 | 0.7448 |
| 0.9599 | 8.33 | 1200 | 1.0594 | 0.7134 |
| 0.675 | 9.72 | 1400 | 0.9321 | 0.6404 |
| 0.4775 | 11.11 | 1600 | 0.9088 | 0.5911 |
| 0.3479 | 12.5 | 1800 | 0.9430 | 0.6010 |
| 0.2712 | 13.89 | 2000 | 0.8948 | 0.5854 |
| 0.2283 | 15.28 | 2200 | 0.9009 | 0.5495 |
| 0.1825 | 16.67 | 2400 | 0.9079 | 0.5501 |
| 0.161 | 18.06 | 2600 | 0.9518 | 0.5390 |
| 0.1394 | 19.44 | 2800 | 0.9529 | 0.5399 |
| 0.1266 | 20.83 | 3000 | 0.9505 | 0.5283 |
| 0.1102 | 22.22 | 3200 | 0.9748 | 0.5328 |
| 0.101 | 23.61 | 3400 | 0.9593 | 0.5316 |
| 0.0907 | 25.0 | 3600 | 0.9832 | 0.5292 |
| 0.0833 | 26.39 | 3800 | 0.9773 | 0.5181 |
| 0.0781 | 27.78 | 4000 | 0.9736 | 0.5163 |
| 0.0744 | 29.17 | 4200 | 0.9752 | 0.5196 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 2.6.1
- Tokenizers 0.13.1
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