transformers 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: ft_0131_kor_eng
  results: []
---

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# ft_0131_kor_eng

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5441
- Cer: 0.0980

## 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.6525        | 0.24  | 500   | 4.2248          | 1.0    |
| 2.7344        | 0.48  | 1000  | 1.6790          | 0.5047 |
| 1.2753        | 0.72  | 1500  | 0.7988          | 0.1950 |
| 0.8951        | 0.96  | 2000  | 0.6650          | 0.1611 |
| 0.7622        | 1.2   | 2500  | 0.6036          | 0.1453 |
| 0.6851        | 1.44  | 3000  | 0.5689          | 0.1384 |
| 0.6464        | 1.68  | 3500  | 0.5471          | 0.1315 |
| 0.6219        | 1.92  | 4000  | 0.5334          | 0.1261 |
| 0.5558        | 2.16  | 4500  | 0.5340          | 0.1255 |
| 0.5121        | 2.41  | 5000  | 0.5098          | 0.1243 |
| 0.509         | 2.65  | 5500  | 0.5241          | 0.1217 |
| 0.51          | 2.89  | 6000  | 0.4947          | 0.1181 |
| 0.4499        | 3.13  | 6500  | 0.5327          | 0.1168 |
| 0.4484        | 3.37  | 7000  | 0.4865          | 0.1158 |
| 0.434         | 3.61  | 7500  | 0.4708          | 0.1169 |
| 0.4316        | 3.85  | 8000  | 0.4781          | 0.1127 |
| 0.399         | 4.09  | 8500  | 0.5105          | 0.1137 |
| 0.3889        | 4.33  | 9000  | 0.4750          | 0.1099 |
| 0.3741        | 4.57  | 9500  | 0.4841          | 0.1124 |
| 0.3837        | 4.81  | 10000 | 0.4879          | 0.1112 |
| 0.3708        | 5.05  | 10500 | 0.4899          | 0.1124 |
| 0.3307        | 5.29  | 11000 | 0.5045          | 0.1090 |
| 0.3431        | 5.53  | 11500 | 0.4755          | 0.1102 |
| 0.333         | 5.77  | 12000 | 0.4579          | 0.1103 |
| 0.3415        | 6.01  | 12500 | 0.5191          | 0.1080 |
| 0.2997        | 6.25  | 13000 | 0.4742          | 0.1085 |
| 0.3087        | 6.49  | 13500 | 0.5069          | 0.1092 |
| 0.303         | 6.73  | 14000 | 0.4754          | 0.1092 |
| 0.3077        | 6.97  | 14500 | 0.4999          | 0.1095 |
| 0.2758        | 7.22  | 15000 | 0.4894          | 0.1073 |
| 0.2743        | 7.46  | 15500 | 0.4973          | 0.1045 |
| 0.2818        | 7.7   | 16000 | 0.4817          | 0.1078 |
| 0.2746        | 7.94  | 16500 | 0.4788          | 0.1058 |
| 0.2508        | 8.18  | 17000 | 0.4743          | 0.1070 |
| 0.2526        | 8.42  | 17500 | 0.5032          | 0.1036 |
| 0.2586        | 8.66  | 18000 | 0.4616          | 0.1049 |
| 0.2534        | 8.9   | 18500 | 0.4569          | 0.1078 |
| 0.2331        | 9.14  | 19000 | 0.4889          | 0.1044 |
| 0.2324        | 9.38  | 19500 | 0.4783          | 0.1040 |
| 0.2444        | 9.62  | 20000 | 0.4836          | 0.1057 |
| 0.2334        | 9.86  | 20500 | 0.4749          | 0.1060 |
| 0.2278        | 10.1  | 21000 | 0.4877          | 0.1041 |
| 0.2048        | 10.34 | 21500 | 0.4940          | 0.1036 |
| 0.2149        | 10.58 | 22000 | 0.4963          | 0.1043 |
| 0.2069        | 10.82 | 22500 | 0.5082          | 0.1028 |
| 0.2049        | 11.06 | 23000 | 0.5214          | 0.1042 |
| 0.1906        | 11.3  | 23500 | 0.5023          | 0.1045 |
| 0.1997        | 11.54 | 24000 | 0.5035          | 0.1013 |
| 0.1933        | 11.78 | 24500 | 0.5121          | 0.1029 |
| 0.1965        | 12.03 | 25000 | 0.5307          | 0.1046 |
| 0.1814        | 12.27 | 25500 | 0.5169          | 0.1039 |
| 0.1774        | 12.51 | 26000 | 0.5022          | 0.1019 |
| 0.1784        | 12.75 | 26500 | 0.5129          | 0.1032 |
| 0.1807        | 12.99 | 27000 | 0.4875          | 0.1019 |
| 0.1704        | 13.23 | 27500 | 0.4937          | 0.1029 |
| 0.1628        | 13.47 | 28000 | 0.5232          | 0.1032 |
| 0.1578        | 13.71 | 28500 | 0.5100          | 0.1019 |
| 0.1594        | 13.95 | 29000 | 0.5183          | 0.0993 |
| 0.162         | 14.19 | 29500 | 0.5220          | 0.1030 |
| 0.1564        | 14.43 | 30000 | 0.5304          | 0.1009 |
| 0.1514        | 14.67 | 30500 | 0.5265          | 0.1009 |
| 0.157         | 14.91 | 31000 | 0.5193          | 0.1011 |
| 0.1401        | 15.15 | 31500 | 0.5608          | 0.1022 |
| 0.1416        | 15.39 | 32000 | 0.5208          | 0.1016 |
| 0.1472        | 15.63 | 32500 | 0.5275          | 0.1011 |
| 0.1415        | 15.87 | 33000 | 0.5314          | 0.1005 |
| 0.1438        | 16.11 | 33500 | 0.5321          | 0.1016 |
| 0.1304        | 16.35 | 34000 | 0.5244          | 0.1020 |
| 0.135         | 16.59 | 34500 | 0.5379          | 0.1005 |
| 0.1352        | 16.84 | 35000 | 0.5279          | 0.0998 |
| 0.1305        | 17.08 | 35500 | 0.5386          | 0.0985 |
| 0.1273        | 17.32 | 36000 | 0.5349          | 0.0992 |
| 0.1252        | 17.56 | 36500 | 0.5348          | 0.0990 |
| 0.1232        | 17.8  | 37000 | 0.5322          | 0.0982 |
| 0.1284        | 18.04 | 37500 | 0.5403          | 0.0985 |
| 0.1181        | 18.28 | 38000 | 0.5344          | 0.0987 |
| 0.123         | 18.52 | 38500 | 0.5333          | 0.0983 |
| 0.112         | 18.76 | 39000 | 0.5424          | 0.0978 |
| 0.1172        | 19.0  | 39500 | 0.5356          | 0.0990 |
| 0.1169        | 19.24 | 40000 | 0.5410          | 0.0984 |
| 0.1125        | 19.48 | 40500 | 0.5416          | 0.0980 |
| 0.1081        | 19.72 | 41000 | 0.5448          | 0.0981 |
| 0.12          | 19.96 | 41500 | 0.5441          | 0.0980 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
