transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-xls-r-300m license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-korean_y_freq
  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. -->

# wav2vec2-large-xls-r-300m-korean_y_freq

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4522
- Cer: 13.5023

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 35.2803       | 0.13  | 200  | 5.5453          | 100.0   |
| 4.6452        | 0.26  | 400  | 4.6065          | 100.0   |
| 4.5568        | 0.39  | 600  | 4.5732          | 97.9643 |
| 4.492         | 0.52  | 800  | 4.5091          | 97.9643 |
| 4.343         | 0.64  | 1000 | 4.2369          | 95.5012 |
| 3.3778        | 0.77  | 1200 | 2.7151          | 49.3917 |
| 2.4127        | 0.9   | 1400 | 2.2297          | 42.1509 |
| 2.0113        | 1.03  | 1600 | 1.8500          | 35.5926 |
| 1.7037        | 1.16  | 1800 | 1.5783          | 31.7942 |
| 1.502         | 1.29  | 2000 | 1.4251          | 29.2184 |
| 1.3376        | 1.42  | 2200 | 1.3812          | 30.4232 |
| 1.2586        | 1.55  | 2400 | 1.1952          | 25.6751 |
| 1.1415        | 1.68  | 2600 | 1.1614          | 25.8176 |
| 1.0858        | 1.81  | 2800 | 1.0985          | 24.9154 |
| 0.9846        | 1.93  | 3000 | 0.9985          | 21.8826 |
| 0.9443        | 2.06  | 3200 | 0.8759          | 19.9359 |
| 0.8298        | 2.19  | 3400 | 0.8549          | 19.5798 |
| 0.8111        | 2.32  | 3600 | 0.8271          | 22.2506 |
| 0.7507        | 2.45  | 3800 | 0.7808          | 20.9389 |
| 0.7202        | 2.58  | 4000 | 0.7409          | 19.5323 |
| 0.7121        | 2.71  | 4200 | 0.7139          | 18.5649 |
| 0.6639        | 2.84  | 4400 | 0.6726          | 17.4669 |
| 0.6595        | 2.97  | 4600 | 0.6830          | 16.6301 |
| 0.6161        | 3.09  | 4800 | 0.6334          | 15.5677 |
| 0.5604        | 3.22  | 5000 | 0.5943          | 14.4460 |
| 0.5387        | 3.35  | 5200 | 0.6169          | 15.4727 |
| 0.5317        | 3.48  | 5400 | 0.5831          | 15.0751 |
| 0.5171        | 3.61  | 5600 | 0.5414          | 14.3807 |
| 0.5           | 3.74  | 5800 | 0.5307          | 14.1789 |
| 0.4888        | 3.87  | 6000 | 0.5171          | 14.4875 |
| 0.4826        | 4.0   | 6200 | 0.5011          | 13.9712 |
| 0.4311        | 4.13  | 6400 | 0.5131          | 14.2679 |
| 0.4178        | 4.26  | 6600 | 0.4929          | 14.0364 |
| 0.3999        | 4.38  | 6800 | 0.4791          | 14.3451 |
| 0.4029        | 4.51  | 7000 | 0.4885          | 13.8584 |
| 0.3922        | 4.64  | 7200 | 0.4759          | 14.2323 |
| 0.3804        | 4.77  | 7400 | 0.4584          | 13.6091 |
| 0.3748        | 4.9   | 7600 | 0.4522          | 13.5023 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
