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---
tags:
- automatic-speech-recognition
- kresnik/zeroth_korean
- generated_from_trainer
datasets:
- zeroth_korean
metrics:
- wer
model-index:
- name: output
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. -->
# output
This model is a fine-tuned version of [/home/son/Work/wav2vec2-xls-r-300m/facebook/wav2vec2-xls-r-300m](https://huggingface.co//home/son/Work/wav2vec2-xls-r-300m/facebook/wav2vec2-xls-r-300m) on the KRESNIK/ZEROTH_KOREAN - CLEAN dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1666
- Wer: 0.9737
- Cer: 0.5039
## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 19.558 | 1.44 | 500 | 19.4094 | 1.0 | 1.0 |
| 4.7968 | 2.87 | 1000 | 4.7828 | 1.0 | 1.0 |
| 4.5125 | 4.31 | 1500 | 4.4959 | 0.9991 | 0.9540 |
| 4.2202 | 5.75 | 2000 | 4.2905 | 0.9923 | 0.8520 |
| 3.7774 | 7.18 | 2500 | 3.2846 | 1.0356 | 0.6652 |
| 3.1418 | 8.62 | 3000 | 2.3624 | 0.9882 | 0.5429 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.1
- Datasets 2.6.1
- Tokenizers 0.11.0
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