---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-l1107
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-korean-colab_v2
  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. -->

# wav2vec2-large-mms-1b-korean-colab_v2

This model is a fine-tuned version of [facebook/mms-1b-l1107](https://huggingface.co/facebook/mms-1b-l1107) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1650
- Wer: 0.3776

## 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: 0.005
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.6667        | 0.18  | 100  | 0.8024          | 0.8379 |
| 0.5754        | 0.36  | 200  | 0.3907          | 0.6495 |
| 0.4658        | 0.53  | 300  | 0.3620          | 0.6224 |
| 0.4321        | 0.71  | 400  | 0.3184          | 0.5842 |
| 0.399         | 0.89  | 500  | 0.2930          | 0.5120 |
| 0.3538        | 1.07  | 600  | 0.2446          | 0.4698 |
| 0.3379        | 1.24  | 700  | 0.2341          | 0.4692 |
| 0.3333        | 1.42  | 800  | 0.2121          | 0.4488 |
| 0.31          | 1.6   | 900  | 0.2054          | 0.4297 |
| 0.3049        | 1.78  | 1000 | 0.1958          | 0.4180 |
| 0.2885        | 1.95  | 1100 | 0.1885          | 0.4143 |
| 0.2632        | 2.13  | 1200 | 0.1865          | 0.4094 |
| 0.2592        | 2.31  | 1300 | 0.1774          | 0.3853 |
| 0.2591        | 2.49  | 1400 | 0.1700          | 0.3924 |
| 0.2605        | 2.66  | 1500 | 0.1701          | 0.3789 |
| 0.2361        | 2.84  | 1600 | 0.1650          | 0.3776 |


### Framework versions

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