---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- zeroth_korean
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-fine-tune_korean_byAILAB
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: zeroth_korean
      type: zeroth_korean
      config: clean
      split: test
      args: clean
    metrics:
    - name: Wer
      type: wer
      value: 0.8577021532901672
---

<!-- 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. -->

# wav2vec2-large-xlsr-53-fine-tune_korean_byAILAB

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the zeroth_korean dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4406
- Wer: 0.8577

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.99  | 38   | 54.3133         | 1.0    |
| No log        | 2.0   | 77   | 33.5397         | 1.0    |
| No log        | 2.99  | 115  | 19.6459         | 1.0    |
| No log        | 4.0   | 154  | 11.1346         | 1.0    |
| No log        | 4.99  | 192  | 5.8854          | 1.0    |
| No log        | 6.0   | 231  | 4.8784          | 1.0    |
| No log        | 6.99  | 269  | 4.8369          | 1.0    |
| No log        | 8.0   | 308  | 4.8535          | 1.0    |
| No log        | 8.99  | 346  | 4.8388          | 1.0    |
| No log        | 10.0  | 385  | 4.8360          | 1.0    |
| 15.1801       | 10.99 | 423  | 4.7653          | 1.0    |
| 15.1801       | 12.0  | 462  | 4.7385          | 1.0    |
| 15.1801       | 12.99 | 500  | 4.6927          | 0.9989 |
| 15.1801       | 14.0  | 539  | 4.6673          | 0.9991 |
| 15.1801       | 14.99 | 577  | 4.6948          | 0.9991 |
| 15.1801       | 16.0  | 616  | 4.6713          | 0.9991 |
| 15.1801       | 16.99 | 654  | 4.6603          | 1.0    |
| 15.1801       | 18.0  | 693  | 4.6428          | 0.9995 |
| 15.1801       | 18.99 | 731  | 4.6520          | 0.9994 |
| 15.1801       | 20.0  | 770  | 4.6554          | 0.9967 |
| 4.3888        | 20.99 | 808  | 4.6054          | 0.9998 |
| 4.3888        | 22.0  | 847  | 4.5723          | 0.9976 |
| 4.3888        | 22.99 | 885  | 4.4586          | 0.9967 |
| 4.3888        | 24.0  | 924  | 4.2547          | 0.9934 |
| 4.3888        | 24.99 | 962  | 3.6554          | 0.9931 |
| 4.3888        | 26.0  | 1001 | 2.8387          | 1.0084 |
| 4.3888        | 26.99 | 1039 | 2.4191          | 1.0551 |
| 4.3888        | 28.0  | 1078 | 2.0997          | 1.0197 |
| 4.3888        | 28.99 | 1116 | 2.0103          | 1.0176 |
| 4.3888        | 30.0  | 1155 | 1.8189          | 0.9461 |
| 4.3888        | 30.99 | 1193 | 1.7623          | 0.9726 |
| 2.7217        | 32.0  | 1232 | 1.7383          | 0.9976 |
| 2.7217        | 32.99 | 1270 | 1.6522          | 0.9584 |
| 2.7217        | 34.0  | 1309 | 1.5558          | 0.9193 |
| 2.7217        | 34.99 | 1347 | 1.5811          | 0.9440 |
| 2.7217        | 36.0  | 1386 | 1.5208          | 0.9158 |
| 2.7217        | 36.99 | 1424 | 1.5088          | 0.9038 |
| 2.7217        | 38.0  | 1463 | 1.5039          | 0.9086 |
| 2.7217        | 38.99 | 1501 | 1.4853          | 0.8987 |
| 2.7217        | 40.0  | 1540 | 1.4799          | 0.8847 |
| 2.7217        | 40.99 | 1578 | 1.4259          | 0.8694 |
| 0.7635        | 42.0  | 1617 | 1.4878          | 0.8883 |
| 0.7635        | 42.99 | 1655 | 1.4394          | 0.8693 |
| 0.7635        | 44.0  | 1694 | 1.4623          | 0.8743 |
| 0.7635        | 44.99 | 1732 | 1.4495          | 0.8710 |
| 0.7635        | 46.0  | 1771 | 1.4463          | 0.8655 |
| 0.7635        | 46.99 | 1809 | 1.4553          | 0.8704 |
| 0.7635        | 48.0  | 1848 | 1.4500          | 0.8646 |
| 0.7635        | 48.99 | 1886 | 1.4387          | 0.8566 |
| 0.7635        | 49.35 | 1900 | 1.4406          | 0.8577 |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.13.3