---
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-xlsr5
  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-xlsr5

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: 0.4067
- Cer: 0.1077

## 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: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.4452        | 0.97  | 1800  | 0.9257          | 0.2337 |
| 1.0684        | 1.95  | 3600  | 0.6873          | 0.1834 |
| 0.9269        | 2.92  | 5400  | 0.5857          | 0.1599 |
| 0.8264        | 3.9   | 7200  | 0.5357          | 0.1442 |
| 0.7637        | 4.87  | 9000  | 0.5069          | 0.1365 |
| 0.7033        | 5.85  | 10800 | 0.4744          | 0.1277 |
| 0.652         | 6.82  | 12600 | 0.4477          | 0.1210 |
| 0.5999        | 7.8   | 14400 | 0.4310          | 0.1144 |
| 0.5606        | 8.77  | 16200 | 0.4150          | 0.1114 |
| 0.5371        | 9.75  | 18000 | 0.4068          | 0.1085 |


### Framework versions

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