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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- zeroth_korean
metrics:
- wer
model-index:
- name: wav2vec2-large-xlrs-korean-v5
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: zeroth_korean
type: zeroth_korean
config: clean
split: None
args: clean
metrics:
- type: wer
value: 0.2433368468604126
name: Wer
---
<!-- 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-xlrs-korean-v5
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the zeroth_korean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1300
- Wer: 0.2433
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|
| 5.1453 | 1.4368 | 500 | 3.1530 | 1.0 |
| 2.4287 | 2.8736 | 1000 | 0.6084 | 0.8317 |
| 0.5556 | 4.3103 | 1500 | 0.3414 | 0.6165 |
| 0.3929 | 5.7471 | 2000 | 0.2729 | 0.5386 |
| 0.3211 | 7.1839 | 2500 | 0.2294 | 0.4794 |
| 0.281 | 8.6207 | 3000 | 0.2052 | 0.4298 |
| 0.2483 | 10.0575 | 3500 | 0.1911 | 0.4061 |
| 0.2243 | 11.4943 | 4000 | 0.1685 | 0.3873 |
| 0.2023 | 12.9310 | 4500 | 0.1627 | 0.3524 |
| 0.188 | 14.3678 | 5000 | 0.1572 | 0.3272 |
| 0.1784 | 15.8046 | 5500 | 0.1495 | 0.3131 |
| 0.1677 | 17.2414 | 6000 | 0.1424 | 0.2881 |
| 0.1533 | 18.6782 | 6500 | 0.1418 | 0.2709 |
| 0.1501 | 20.1149 | 7000 | 0.1387 | 0.2822 |
| 0.1402 | 21.5517 | 7500 | 0.1401 | 0.2697 |
| 0.1353 | 22.9885 | 8000 | 0.1367 | 0.2643 |
| 0.133 | 24.4253 | 8500 | 0.1337 | 0.2578 |
| 0.1254 | 25.8621 | 9000 | 0.1355 | 0.2560 |
| 0.1262 | 27.2989 | 9500 | 0.1339 | 0.2474 |
| 0.121 | 28.7356 | 10000 | 0.1300 | 0.2433 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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