---
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: 0.5172
- Cer: 0.1076

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.742         | 2.6   | 1500  | 0.9038          | 0.2330 |
| 0.9228        | 5.2   | 3000  | 0.6193          | 0.1656 |
| 0.6805        | 7.8   | 4500  | 0.5522          | 0.1481 |
| 0.5577        | 10.4  | 6000  | 0.5136          | 0.1349 |
| 0.4797        | 13.0  | 7500  | 0.5074          | 0.1312 |
| 0.4161        | 15.6  | 9000  | 0.4959          | 0.1243 |
| 0.3701        | 18.21 | 10500 | 0.4948          | 0.1224 |
| 0.3307        | 20.81 | 12000 | 0.4881          | 0.1199 |
| 0.2946        | 23.41 | 13500 | 0.4970          | 0.1179 |
| 0.2636        | 26.01 | 15000 | 0.4950          | 0.1145 |
| 0.2367        | 28.61 | 16500 | 0.4905          | 0.1119 |
| 0.2157        | 31.21 | 18000 | 0.5066          | 0.1110 |
| 0.1979        | 33.81 | 19500 | 0.5133          | 0.1103 |
| 0.1808        | 36.41 | 21000 | 0.5160          | 0.1091 |
| 0.17          | 39.01 | 22500 | 0.5129          | 0.1074 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0