---
license: cc-by-nc-4.0
base_model: weekcircle/wav2vec2-large-mms-1b-korean-colab
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-korean-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ko
      split: test
      args: ko
    metrics:
    - name: Wer
      type: wer
      value: 0.9959718026183283
---

<!-- 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-mms-1b-korean-colab

This model is a fine-tuned version of [weekcircle/wav2vec2-large-mms-1b-korean-colab](https://huggingface.co/weekcircle/wav2vec2-large-mms-1b-korean-colab) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 8.8258
- Wer: 0.9960

## 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: 0.001
- train_batch_size: 8
- 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: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.4313        | 2.63  | 100  | 7.9123          | 0.9839 |
| 2.3616        | 5.26  | 200  | 7.9118          | 0.9930 |
| 1.859         | 7.89  | 300  | 7.9977          | 0.9909 |
| 1.4135        | 10.53 | 400  | 8.3395          | 1.0040 |
| 1.1407        | 13.16 | 500  | 8.5900          | 0.9940 |
| 0.9639        | 15.79 | 600  | 8.6300          | 0.9950 |
| 0.7991        | 18.42 | 700  | 8.8258          | 0.9960 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3