---
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_byAILAB2
  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: 0.9067911459117602
---

<!-- 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_byAILAB2

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: 1.4929
- Wer: 0.9068

## 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: 0.0002
- 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   | 54.4059         | 1.0    |
| No log        | 2.0   | 77   | 38.8388         | 1.0    |
| No log        | 2.99  | 115  | 24.1740         | 1.0    |
| No log        | 4.0   | 154  | 16.4733         | 1.0    |
| No log        | 4.99  | 192  | 10.1900         | 1.0    |
| No log        | 6.0   | 231  | 6.0076          | 1.0    |
| No log        | 6.99  | 269  | 4.8990          | 1.0    |
| No log        | 8.0   | 308  | 4.8442          | 1.0    |
| No log        | 8.99  | 346  | 4.8284          | 1.0    |
| No log        | 10.0  | 385  | 4.8316          | 1.0    |
| 16.886        | 10.99 | 423  | 4.8164          | 1.0    |
| 16.886        | 12.0  | 462  | 4.7815          | 1.0    |
| 16.886        | 12.99 | 500  | 4.7204          | 0.9989 |
| 16.886        | 14.0  | 539  | 4.6842          | 0.9989 |
| 16.886        | 14.99 | 577  | 4.6641          | 0.9994 |
| 16.886        | 16.0  | 616  | 4.6527          | 1.0    |
| 16.886        | 16.99 | 654  | 4.6745          | 0.9992 |
| 16.886        | 18.0  | 693  | 4.6591          | 1.0    |
| 16.886        | 18.99 | 731  | 4.6506          | 0.9997 |
| 16.886        | 20.0  | 770  | 4.6719          | 0.9967 |
| 4.4391        | 20.99 | 808  | 4.6067          | 0.9968 |
| 4.4391        | 22.0  | 847  | 4.5748          | 0.9968 |
| 4.4391        | 22.99 | 885  | 4.5166          | 0.9962 |
| 4.4391        | 24.0  | 924  | 4.3783          | 0.9926 |
| 4.4391        | 24.99 | 962  | 4.2711          | 0.9913 |
| 4.4391        | 26.0  | 1001 | 3.6515          | 1.0030 |
| 4.4391        | 26.99 | 1039 | 3.1057          | 1.0640 |
| 4.4391        | 28.0  | 1078 | 2.6593          | 1.0742 |
| 4.4391        | 28.99 | 1116 | 2.4071          | 1.0587 |
| 4.4391        | 30.0  | 1155 | 2.2041          | 1.0379 |
| 4.4391        | 30.99 | 1193 | 2.0495          | 1.0319 |
| 3.1722        | 32.0  | 1232 | 1.9754          | 1.0459 |
| 3.1722        | 32.99 | 1270 | 1.8658          | 0.9968 |
| 3.1722        | 34.0  | 1309 | 1.7887          | 0.9883 |
| 3.1722        | 34.99 | 1347 | 1.7560          | 0.9776 |
| 3.1722        | 36.0  | 1386 | 1.6987          | 0.9675 |
| 3.1722        | 36.99 | 1424 | 1.6513          | 0.9443 |
| 3.1722        | 38.0  | 1463 | 1.6187          | 0.9473 |
| 3.1722        | 38.99 | 1501 | 1.6210          | 0.9408 |
| 3.1722        | 40.0  | 1540 | 1.5957          | 0.9458 |
| 3.1722        | 40.99 | 1578 | 1.5673          | 0.9246 |
| 1.2364        | 42.0  | 1617 | 1.5748          | 0.9286 |
| 1.2364        | 42.99 | 1655 | 1.5333          | 0.9217 |
| 1.2364        | 44.0  | 1694 | 1.5138          | 0.9100 |
| 1.2364        | 44.99 | 1732 | 1.5244          | 0.9223 |
| 1.2364        | 46.0  | 1771 | 1.5041          | 0.9080 |
| 1.2364        | 46.99 | 1809 | 1.5151          | 0.9155 |
| 1.2364        | 48.0  | 1848 | 1.4955          | 0.9077 |
| 1.2364        | 48.99 | 1886 | 1.4924          | 0.9065 |
| 1.2364        | 49.35 | 1900 | 1.4929          | 0.9068 |


### Framework versions

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