---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
model-index:
- name: ko-xlsr
  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. -->

# ko-xlsr

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the ./SAMPLE_SPEECH.PY - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5156
- Cer: 0.1228

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.778         | 3.31  | 1000  | 1.2773          | 0.3050 |
| 1.1037        | 6.63  | 2000  | 0.7716          | 0.1888 |
| 0.9529        | 9.94  | 3000  | 0.6726          | 0.1659 |
| 0.8424        | 13.26 | 4000  | 0.6138          | 0.1512 |
| 0.767         | 16.57 | 5000  | 0.5885          | 0.1433 |
| 0.7201        | 19.88 | 6000  | 0.5682          | 0.1378 |
| 0.664         | 23.2  | 7000  | 0.5583          | 0.1333 |
| 0.6296        | 26.51 | 8000  | 0.5416          | 0.1298 |
| 0.6021        | 29.83 | 9000  | 0.5377          | 0.1272 |
| 0.568         | 33.14 | 10000 | 0.5241          | 0.1246 |
| 0.5519        | 36.45 | 11000 | 0.5184          | 0.1228 |
| 0.5395        | 39.77 | 12000 | 0.5156          | 0.1227 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3