---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- ./sample_speech.py
- generated_from_trainer
metrics:
- wer
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: 0.4228
- Cer: 0.1091
- Wer: 0.3025

## 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: 4
- total_train_batch_size: 64
- 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: 1000
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.5566        | 0.94  | 2000  | 1.0226          | 0.2632 | 0.6184 |
| 1.179         | 1.89  | 4000  | 0.7682          | 0.2001 | 0.4990 |
| 1.0432        | 2.83  | 6000  | 0.6633          | 0.1749 | 0.4516 |
| 0.9413        | 3.77  | 8000  | 0.6159          | 0.1624 | 0.4259 |
| 0.8765        | 4.72  | 10000 | 0.5792          | 0.1538 | 0.4061 |
| 0.8248        | 5.66  | 12000 | 0.5456          | 0.1446 | 0.3877 |
| 0.7714        | 6.6   | 14000 | 0.5316          | 0.1397 | 0.3710 |
| 0.7388        | 7.55  | 16000 | 0.5172          | 0.1356 | 0.3657 |
| 0.6912        | 8.49  | 18000 | 0.4892          | 0.1291 | 0.3508 |
| 0.6549        | 9.43  | 20000 | 0.4694          | 0.1241 | 0.3397 |
| 0.614         | 10.37 | 22000 | 0.4615          | 0.1205 | 0.3309 |
| 0.5901        | 11.32 | 24000 | 0.4489          | 0.1177 | 0.3215 |
| 0.555         | 12.26 | 26000 | 0.4419          | 0.1148 | 0.3163 |
| 0.5377        | 13.2  | 28000 | 0.4320          | 0.1122 | 0.3103 |
| 0.5253        | 14.15 | 30000 | 0.4251          | 0.1102 | 0.3052 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1