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# ft_0202_korean

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: 0.5641
- Cer: 0.0886

## 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: 4
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 24.8667       | 0.1   | 500   | 5.1486          | 1.0    |
| 4.7502        | 0.2   | 1000  | 4.8664          | 1.0    |
| 4.6253        | 0.31  | 1500  | 4.6545          | 1.0    |
| 4.4689        | 0.41  | 2000  | 4.2926          | 0.9784 |
| 3.5162        | 0.51  | 2500  | 2.6778          | 0.5191 |
| 2.6355        | 0.61  | 3000  | 2.1095          | 0.4424 |
| 2.2199        | 0.72  | 3500  | 1.7898          | 0.3896 |
| 2.0362        | 0.82  | 4000  | 1.5788          | 0.3551 |
| 1.8016        | 0.92  | 4500  | 1.4385          | 0.3407 |
| 1.6906        | 1.02  | 5000  | 1.3008          | 0.3072 |
| 1.5136        | 1.12  | 5500  | 1.1820          | 0.2845 |
| 1.4168        | 1.23  | 6000  | 1.0870          | 0.2673 |
| 1.3461        | 1.33  | 6500  | 1.0315          | 0.2589 |
| 1.3039        | 1.43  | 7000  | 0.9758          | 0.2438 |
| 1.2616        | 1.53  | 7500  | 0.9589          | 0.2415 |
| 1.2301        | 1.64  | 8000  | 0.9262          | 0.2275 |
| 1.1979        | 1.74  | 8500  | 0.8997          | 0.2305 |
| 1.1518        | 1.84  | 9000  | 0.8420          | 0.2183 |
| 1.0925        | 1.94  | 9500  | 0.8073          | 0.2103 |
| 1.051         | 2.04  | 10000 | 0.7964          | 0.2050 |
| 1.0025        | 2.15  | 10500 | 0.7683          | 0.2017 |
| 0.9649        | 2.25  | 11000 | 0.7426          | 0.1984 |
| 0.9574        | 2.35  | 11500 | 0.7213          | 0.1919 |
| 0.9244        | 2.45  | 12000 | 0.7198          | 0.1939 |
| 0.9334        | 2.56  | 12500 | 0.6958          | 0.1847 |
| 0.8901        | 2.66  | 13000 | 0.6925          | 0.1829 |
| 0.9049        | 2.76  | 13500 | 0.6862          | 0.1819 |
| 0.8834        | 2.86  | 14000 | 0.6751          | 0.1813 |
| 0.8691        | 2.97  | 14500 | 0.6659          | 0.1744 |
| 0.8194        | 3.07  | 15000 | 0.6674          | 0.1740 |
| 0.7972        | 3.17  | 15500 | 0.6612          | 0.1711 |
| 0.7737        | 3.27  | 16000 | 0.6474          | 0.1719 |
| 0.76          | 3.37  | 16500 | 0.6760          | 0.1687 |
| 0.7744        | 3.48  | 17000 | 0.6232          | 0.1645 |
| 0.7571        | 3.58  | 17500 | 0.6104          | 0.1607 |
| 0.753         | 3.68  | 18000 | 0.6099          | 0.1609 |
| 0.7276        | 3.78  | 18500 | 0.5977          | 0.1562 |
| 0.7388        | 3.89  | 19000 | 0.5798          | 0.1548 |
| 0.7173        | 3.99  | 19500 | 0.5894          | 0.1547 |
| 0.6796        | 4.09  | 20000 | 0.5873          | 0.1537 |
| 0.6549        | 4.19  | 20500 | 0.5852          | 0.1518 |
| 0.6534        | 4.29  | 21000 | 0.5859          | 0.1502 |
| 0.6659        | 4.4   | 21500 | 0.5679          | 0.1474 |
| 0.654         | 4.5   | 22000 | 0.5804          | 0.1490 |
| 0.6356        | 4.6   | 22500 | 0.5888          | 0.1504 |
| 0.6612        | 4.7   | 23000 | 0.5544          | 0.1436 |
| 0.6344        | 4.81  | 23500 | 0.5641          | 0.1428 |
| 0.6432        | 4.91  | 24000 | 0.5570          | 0.1417 |
| 0.6297        | 5.01  | 24500 | 0.5638          | 0.1413 |
| 0.5746        | 5.11  | 25000 | 0.5808          | 0.1435 |
| 0.5619        | 5.21  | 25500 | 0.5471          | 0.1403 |
| 0.5835        | 5.32  | 26000 | 0.5505          | 0.1417 |
| 0.5867        | 5.42  | 26500 | 0.5446          | 0.1361 |
| 0.5598        | 5.52  | 27000 | 0.5558          | 0.1358 |
| 0.5465        | 5.62  | 27500 | 0.5434          | 0.1354 |
| 0.546         | 5.73  | 28000 | 0.5394          | 0.1362 |
| 0.5527        | 5.83  | 28500 | 0.5289          | 0.1334 |
| 0.5712        | 5.93  | 29000 | 0.5175          | 0.1321 |
| 0.5308        | 6.03  | 29500 | 0.5279          | 0.1318 |
| 0.5093        | 6.13  | 30000 | 0.5301          | 0.1356 |
| 0.5129        | 6.24  | 30500 | 0.5252          | 0.1302 |
| 0.51          | 6.34  | 31000 | 0.5279          | 0.1302 |
| 0.4938        | 6.44  | 31500 | 0.5234          | 0.1281 |
| 0.5044        | 6.54  | 32000 | 0.5105          | 0.1290 |
| 0.4977        | 6.65  | 32500 | 0.5299          | 0.1262 |
| 0.5046        | 6.75  | 33000 | 0.5164          | 0.1268 |
| 0.4913        | 6.85  | 33500 | 0.5078          | 0.1260 |
| 0.4926        | 6.95  | 34000 | 0.5052          | 0.1252 |
| 0.4636        | 7.06  | 34500 | 0.5200          | 0.1236 |
| 0.4437        | 7.16  | 35000 | 0.5070          | 0.1217 |
| 0.4361        | 7.26  | 35500 | 0.5056          | 0.1238 |
| 0.456         | 7.36  | 36000 | 0.5038          | 0.1212 |
| 0.4458        | 7.46  | 36500 | 0.5101          | 0.1218 |
| 0.441         | 7.57  | 37000 | 0.5050          | 0.1211 |
| 0.4477        | 7.67  | 37500 | 0.5054          | 0.1183 |
| 0.4521        | 7.77  | 38000 | 0.5029          | 0.1179 |
| 0.4516        | 7.87  | 38500 | 0.5048          | 0.1211 |
| 0.4466        | 7.98  | 39000 | 0.4962          | 0.1187 |
| 0.4103        | 8.08  | 39500 | 0.5037          | 0.1181 |
| 0.4079        | 8.18  | 40000 | 0.5123          | 0.1188 |
| 0.3871        | 8.28  | 40500 | 0.5027          | 0.1161 |
| 0.4012        | 8.38  | 41000 | 0.4979          | 0.1165 |
| 0.4028        | 8.49  | 41500 | 0.5291          | 0.1190 |
| 0.405         | 8.59  | 42000 | 0.5006          | 0.1164 |
| 0.3916        | 8.69  | 42500 | 0.4994          | 0.1136 |
| 0.4055        | 8.79  | 43000 | 0.4961          | 0.1151 |
| 0.4098        | 8.9   | 43500 | 0.4934          | 0.1127 |
| 0.3983        | 9.0   | 44000 | 0.4873          | 0.1122 |
| 0.3618        | 9.1   | 44500 | 0.4981          | 0.1130 |
| 0.3504        | 9.2   | 45000 | 0.4963          | 0.1116 |
| 0.3507        | 9.3   | 45500 | 0.4998          | 0.1132 |
| 0.37          | 9.41  | 46000 | 0.4787          | 0.1093 |
| 0.3597        | 9.51  | 46500 | 0.4883          | 0.1095 |
| 0.3676        | 9.61  | 47000 | 0.4838          | 0.1096 |
| 0.3469        | 9.71  | 47500 | 0.4967          | 0.1103 |
| 0.3726        | 9.82  | 48000 | 0.4796          | 0.1081 |
| 0.3518        | 9.92  | 48500 | 0.4849          | 0.1093 |
| 0.3444        | 10.02 | 49000 | 0.4902          | 0.1092 |
| 0.3213        | 10.12 | 49500 | 0.5074          | 0.1082 |
| 0.3325        | 10.22 | 50000 | 0.5097          | 0.1092 |
| 0.3289        | 10.33 | 50500 | 0.5087          | 0.1090 |
| 0.3329        | 10.43 | 51000 | 0.5041          | 0.1090 |
| 0.325         | 10.53 | 51500 | 0.4926          | 0.1096 |
| 0.3286        | 10.63 | 52000 | 0.5094          | 0.1058 |
| 0.3339        | 10.74 | 52500 | 0.4896          | 0.1074 |
| 0.32          | 10.84 | 53000 | 0.4862          | 0.1069 |
| 0.3151        | 10.94 | 53500 | 0.4916          | 0.1064 |
| 0.3262        | 11.04 | 54000 | 0.4836          | 0.1049 |
| 0.2925        | 11.15 | 54500 | 0.4971          | 0.1056 |
| 0.2795        | 11.25 | 55000 | 0.5115          | 0.1059 |
| 0.2937        | 11.35 | 55500 | 0.5015          | 0.1058 |
| 0.3031        | 11.45 | 56000 | 0.4892          | 0.1039 |
| 0.3083        | 11.55 | 56500 | 0.5128          | 0.1044 |
| 0.315         | 11.66 | 57000 | 0.4943          | 0.1029 |
| 0.2962        | 11.76 | 57500 | 0.4978          | 0.1020 |
| 0.3018        | 11.86 | 58000 | 0.4841          | 0.1026 |
| 0.2905        | 11.96 | 58500 | 0.5011          | 0.1032 |
| 0.2848        | 12.07 | 59000 | 0.5009          | 0.1010 |
| 0.2618        | 12.17 | 59500 | 0.5169          | 0.1028 |
| 0.2699        | 12.27 | 60000 | 0.4928          | 0.1012 |
| 0.2825        | 12.37 | 60500 | 0.5010          | 0.1022 |
| 0.2723        | 12.47 | 61000 | 0.4960          | 0.1014 |
| 0.2754        | 12.58 | 61500 | 0.5003          | 0.1002 |
| 0.267         | 12.68 | 62000 | 0.4775          | 0.0995 |
| 0.2643        | 12.78 | 62500 | 0.4873          | 0.1003 |
| 0.2704        | 12.88 | 63000 | 0.5097          | 0.1012 |
| 0.2611        | 12.99 | 63500 | 0.5054          | 0.1009 |
| 0.2534        | 13.09 | 64000 | 0.5063          | 0.0996 |
| 0.247         | 13.19 | 64500 | 0.5079          | 0.0989 |
| 0.2358        | 13.29 | 65000 | 0.5029          | 0.0986 |
| 0.2418        | 13.39 | 65500 | 0.5108          | 0.0980 |
| 0.2536        | 13.5  | 66000 | 0.5140          | 0.0980 |
| 0.25          | 13.6  | 66500 | 0.4974          | 0.0973 |
| 0.2489        | 13.7  | 67000 | 0.5047          | 0.0969 |
| 0.2427        | 13.8  | 67500 | 0.5089          | 0.0980 |
| 0.2496        | 13.91 | 68000 | 0.5126          | 0.0980 |
| 0.2572        | 14.01 | 68500 | 0.5071          | 0.0981 |
| 0.2248        | 14.11 | 69000 | 0.5215          | 0.0985 |
| 0.2344        | 14.21 | 69500 | 0.5116          | 0.0974 |
| 0.2245        | 14.31 | 70000 | 0.5185          | 0.0966 |
| 0.2153        | 14.42 | 70500 | 0.5129          | 0.0962 |
| 0.2245        | 14.52 | 71000 | 0.5225          | 0.0964 |
| 0.2229        | 14.62 | 71500 | 0.5194          | 0.0963 |
| 0.2354        | 14.72 | 72000 | 0.5021          | 0.0957 |
| 0.2246        | 14.83 | 72500 | 0.5163          | 0.0955 |
| 0.2154        | 14.93 | 73000 | 0.5114          | 0.0945 |
| 0.2191        | 15.03 | 73500 | 0.5281          | 0.0947 |
| 0.2118        | 15.13 | 74000 | 0.5295          | 0.0939 |
| 0.2161        | 15.24 | 74500 | 0.5131          | 0.0945 |
| 0.2179        | 15.34 | 75000 | 0.5270          | 0.0946 |
| 0.2144        | 15.44 | 75500 | 0.5243          | 0.0945 |
| 0.1999        | 15.54 | 76000 | 0.5212          | 0.0930 |
| 0.213         | 15.64 | 76500 | 0.5365          | 0.0935 |
| 0.215         | 15.75 | 77000 | 0.5188          | 0.0937 |
| 0.2037        | 15.85 | 77500 | 0.5315          | 0.0936 |
| 0.2122        | 15.95 | 78000 | 0.5267          | 0.0939 |
| 0.2084        | 16.05 | 78500 | 0.5306          | 0.0919 |
| 0.1971        | 16.16 | 79000 | 0.5354          | 0.0917 |
| 0.197         | 16.26 | 79500 | 0.5426          | 0.0920 |
| 0.1988        | 16.36 | 80000 | 0.5382          | 0.0920 |
| 0.1904        | 16.46 | 80500 | 0.5396          | 0.0918 |
| 0.1987        | 16.56 | 81000 | 0.5523          | 0.0918 |
| 0.1941        | 16.67 | 81500 | 0.5375          | 0.0919 |
| 0.1879        | 16.77 | 82000 | 0.5460          | 0.0911 |
| 0.202         | 16.87 | 82500 | 0.5436          | 0.0913 |
| 0.1932        | 16.97 | 83000 | 0.5389          | 0.0910 |
| 0.1809        | 17.08 | 83500 | 0.5496          | 0.0912 |
| 0.1933        | 17.18 | 84000 | 0.5587          | 0.0916 |
| 0.1802        | 17.28 | 84500 | 0.5466          | 0.0908 |
| 0.1956        | 17.38 | 85000 | 0.5563          | 0.0907 |
| 0.1838        | 17.48 | 85500 | 0.5579          | 0.0904 |
| 0.1787        | 17.59 | 86000 | 0.5520          | 0.0905 |
| 0.1859        | 17.69 | 86500 | 0.5575          | 0.0901 |
| 0.1864        | 17.79 | 87000 | 0.5640          | 0.0909 |
| 0.1887        | 17.89 | 87500 | 0.5594          | 0.0908 |
| 0.1802        | 18.0  | 88000 | 0.5575          | 0.0905 |
| 0.1769        | 18.1  | 88500 | 0.5528          | 0.0899 |
| 0.1772        | 18.2  | 89000 | 0.5672          | 0.0894 |
| 0.1722        | 18.3  | 89500 | 0.5588          | 0.0897 |
| 0.1714        | 18.4  | 90000 | 0.5604          | 0.0898 |
| 0.1632        | 18.51 | 90500 | 0.5576          | 0.0900 |
| 0.1726        | 18.61 | 91000 | 0.5526          | 0.0897 |
| 0.167         | 18.71 | 91500 | 0.5652          | 0.0897 |
| 0.1851        | 18.81 | 92000 | 0.5603          | 0.0899 |
| 0.1766        | 18.92 | 92500 | 0.5605          | 0.0894 |
| 0.1685        | 19.02 | 93000 | 0.5620          | 0.0892 |
| 0.1732        | 19.12 | 93500 | 0.5679          | 0.0889 |
| 0.166         | 19.22 | 94000 | 0.5655          | 0.0890 |
| 0.1663        | 19.33 | 94500 | 0.5638          | 0.0892 |
| 0.1688        | 19.43 | 95000 | 0.5647          | 0.0892 |
| 0.1613        | 19.53 | 95500 | 0.5661          | 0.0890 |
| 0.1749        | 19.63 | 96000 | 0.5673          | 0.0889 |
| 0.1635        | 19.73 | 96500 | 0.5649          | 0.0887 |
| 0.1647        | 19.84 | 97000 | 0.5641          | 0.0886 |
| 0.1633        | 19.94 | 97500 | 0.5641          | 0.0886 |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/wav2vec2-xls-r-300m", "model-index": [{"name": "ft_0202_korean", "results": []}]}
transformers safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:facebook/wav2vec2-xls-r-300m license:apache-2.0 endpoints_compatible region:us