---
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: 0.4215
- Cer: 0.1103

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.5961        | 0.94  | 2000  | 1.0685          | 0.2712 |
| 1.2068        | 1.89  | 4000  | 0.8059          | 0.2117 |
| 1.0519        | 2.83  | 6000  | 0.6764          | 0.1784 |
| 0.9522        | 3.77  | 8000  | 0.6238          | 0.1667 |
| 0.8855        | 4.72  | 10000 | 0.5901          | 0.1572 |
| 0.8353        | 5.66  | 12000 | 0.5560          | 0.1473 |
| 0.7765        | 6.6   | 14000 | 0.5313          | 0.1418 |
| 0.7333        | 7.55  | 16000 | 0.5100          | 0.1339 |
| 0.6887        | 8.49  | 18000 | 0.4902          | 0.1304 |
| 0.6547        | 9.43  | 20000 | 0.4785          | 0.1252 |
| 0.612         | 10.37 | 22000 | 0.4594          | 0.1200 |
| 0.5855        | 11.32 | 24000 | 0.4469          | 0.1176 |
| 0.5538        | 12.26 | 26000 | 0.4398          | 0.1156 |
| 0.5341        | 13.2  | 28000 | 0.4318          | 0.1124 |
| 0.5229        | 14.15 | 30000 | 0.4251          | 0.1111 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1