---
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