pytorch tensorboard wav2vec2 automatic-speech-recognition transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xlsr-korean-demo-colab_epoch15
  results: []
---

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# wav2vec2-large-xlsr-korean-demo-colab_epoch15

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4133
- Wer: 0.3801

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 16.9017       | 0.8   | 400  | 4.6273          | 1.0    |
| 4.4633        | 1.6   | 800  | 4.4419          | 1.0    |
| 4.2262        | 2.4   | 1200 | 3.8477          | 0.9994 |
| 2.4402        | 3.21  | 1600 | 1.3564          | 0.8111 |
| 1.3499        | 4.01  | 2000 | 0.9070          | 0.6664 |
| 0.9922        | 4.81  | 2400 | 0.7496          | 0.6131 |
| 0.8271        | 5.61  | 2800 | 0.6240          | 0.5408 |
| 0.6918        | 6.41  | 3200 | 0.5506          | 0.5026 |
| 0.6015        | 7.21  | 3600 | 0.5303          | 0.4935 |
| 0.5435        | 8.02  | 4000 | 0.4951          | 0.4696 |
| 0.4584        | 8.82  | 4400 | 0.4677          | 0.4432 |
| 0.4258        | 9.62  | 4800 | 0.4602          | 0.4307 |
| 0.3906        | 10.42 | 5200 | 0.4456          | 0.4195 |
| 0.3481        | 11.22 | 5600 | 0.4265          | 0.4062 |
| 0.3216        | 12.02 | 6000 | 0.4241          | 0.4046 |
| 0.2908        | 12.83 | 6400 | 0.4106          | 0.3941 |
| 0.2747        | 13.63 | 6800 | 0.4146          | 0.3855 |
| 0.2633        | 14.43 | 7200 | 0.4133          | 0.3801 |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.12.0+cu113
- Datasets 1.18.3
- Tokenizers 0.12.1
