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
metrics:
- wer
model-index:
- name: XLS-R_Synthesis_LG_v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# XLS-R_Synthesis_LG_v1

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: 0.2280
- Wer: 0.1054

## 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: 28
- eval_batch_size: 14
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 112
- total_eval_batch_size: 28
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 5.8288        | 1.0   | 738   | 3.2777          | 1.0    |
| 2.5551        | 2.0   | 1476  | 0.9521          | 0.8132 |
| 0.7636        | 3.0   | 2214  | 0.4213          | 0.4841 |
| 0.4823        | 4.0   | 2952  | 0.3358          | 0.3664 |
| 0.3808        | 5.0   | 3690  | 0.2608          | 0.3030 |
| 0.3183        | 6.0   | 4428  | 0.2175          | 0.2567 |
| 0.2771        | 7.0   | 5166  | 0.1981          | 0.2330 |
| 0.2475        | 8.0   | 5904  | 0.1878          | 0.2101 |
| 0.2267        | 9.0   | 6642  | 0.1812          | 0.2042 |
| 0.2091        | 10.0  | 7380  | 0.1721          | 0.1907 |
| 0.1938        | 11.0  | 8118  | 0.1691          | 0.1816 |
| 0.1776        | 12.0  | 8856  | 0.1597          | 0.1730 |
| 0.1679        | 13.0  | 9594  | 0.1558          | 0.1706 |
| 0.1575        | 14.0  | 10332 | 0.1610          | 0.1586 |
| 0.1498        | 15.0  | 11070 | 0.1532          | 0.1535 |
| 0.1421        | 16.0  | 11808 | 0.1544          | 0.1520 |
| 0.1356        | 17.0  | 12546 | 0.1488          | 0.1491 |
| 0.1287        | 18.0  | 13284 | 0.1542          | 0.1470 |
| 0.1239        | 19.0  | 14022 | 0.1484          | 0.1464 |
| 0.1198        | 20.0  | 14760 | 0.1523          | 0.1437 |
| 0.1154        | 21.0  | 15498 | 0.1540          | 0.1390 |
| 0.1103        | 22.0  | 16236 | 0.1484          | 0.1416 |
| 0.107         | 23.0  | 16974 | 0.1506          | 0.1421 |
| 0.1037        | 24.0  | 17712 | 0.1472          | 0.1386 |
| 0.0997        | 25.0  | 18450 | 0.1525          | 0.1382 |
| 0.0966        | 26.0  | 19188 | 0.1541          | 0.1400 |
| 0.095         | 27.0  | 19926 | 0.1595          | 0.1335 |
| 0.0914        | 28.0  | 20664 | 0.1650          | 0.1341 |
| 0.0893        | 29.0  | 21402 | 0.1631          | 0.1375 |
| 0.0855        | 30.0  | 22140 | 0.1700          | 0.1378 |
| 0.083         | 31.0  | 22878 | 0.1629          | 0.1320 |
| 0.0819        | 32.0  | 23616 | 0.1658          | 0.1316 |
| 0.079         | 33.0  | 24354 | 0.1674          | 0.1303 |
| 0.0769        | 34.0  | 25092 | 0.1749          | 0.1304 |
| 0.0755        | 35.0  | 25830 | 0.1755          | 0.1325 |
| 0.0744        | 36.0  | 26568 | 0.1703          | 0.1292 |
| 0.072         | 37.0  | 27306 | 0.1687          | 0.1298 |
| 0.0705        | 38.0  | 28044 | 0.1683          | 0.1298 |
| 0.069         | 39.0  | 28782 | 0.1712          | 0.1299 |
| 0.0668        | 40.0  | 29520 | 0.1798          | 0.1250 |
| 0.0654        | 41.0  | 30258 | 0.1811          | 0.1281 |
| 0.065         | 42.0  | 30996 | 0.1858          | 0.1274 |
| 0.0638        | 43.0  | 31734 | 0.1826          | 0.1250 |
| 0.0614        | 44.0  | 32472 | 0.1822          | 0.1292 |
| 0.0615        | 45.0  | 33210 | 0.1798          | 0.1278 |
| 0.0602        | 46.0  | 33948 | 0.1943          | 0.1237 |
| 0.0596        | 47.0  | 34686 | 0.1793          | 0.1267 |
| 0.0583        | 48.0  | 35424 | 0.1969          | 0.1261 |
| 0.0569        | 49.0  | 36162 | 0.1927          | 0.1215 |
| 0.0558        | 50.0  | 36900 | 0.1974          | 0.1238 |
| 0.0555        | 51.0  | 37638 | 0.1897          | 0.1231 |
| 0.0545        | 52.0  | 38376 | 0.1894          | 0.1242 |
| 0.0534        | 53.0  | 39114 | 0.1937          | 0.1221 |
| 0.0529        | 54.0  | 39852 | 0.1933          | 0.1203 |
| 0.0521        | 55.0  | 40590 | 0.1938          | 0.1221 |
| 0.0507        | 56.0  | 41328 | 0.1897          | 0.1210 |
| 0.0502        | 57.0  | 42066 | 0.2000          | 0.1196 |
| 0.0482        | 58.0  | 42804 | 0.1974          | 0.1185 |
| 0.0481        | 59.0  | 43542 | 0.2058          | 0.1163 |
| 0.0465        | 60.0  | 44280 | 0.1950          | 0.1162 |
| 0.0467        | 61.0  | 45018 | 0.2007          | 0.1170 |
| 0.0457        | 62.0  | 45756 | 0.1955          | 0.1174 |
| 0.0454        | 63.0  | 46494 | 0.2063          | 0.1171 |
| 0.0442        | 64.0  | 47232 | 0.1993          | 0.1170 |
| 0.0438        | 65.0  | 47970 | 0.2038          | 0.1159 |
| 0.0426        | 66.0  | 48708 | 0.2078          | 0.1156 |
| 0.0418        | 67.0  | 49446 | 0.2092          | 0.1161 |
| 0.0415        | 68.0  | 50184 | 0.2108          | 0.1131 |
| 0.0405        | 69.0  | 50922 | 0.2080          | 0.1132 |
| 0.0398        | 70.0  | 51660 | 0.2122          | 0.1127 |
| 0.0391        | 71.0  | 52398 | 0.2117          | 0.1146 |
| 0.0384        | 72.0  | 53136 | 0.2125          | 0.1130 |
| 0.038         | 73.0  | 53874 | 0.2129          | 0.1127 |
| 0.0372        | 74.0  | 54612 | 0.2150          | 0.1130 |
| 0.0365        | 75.0  | 55350 | 0.2110          | 0.1123 |
| 0.0364        | 76.0  | 56088 | 0.2121          | 0.1122 |
| 0.0359        | 77.0  | 56826 | 0.2118          | 0.1125 |
| 0.0354        | 78.0  | 57564 | 0.2146          | 0.1105 |
| 0.035         | 79.0  | 58302 | 0.2192          | 0.1113 |
| 0.0337        | 80.0  | 59040 | 0.2204          | 0.1103 |
| 0.0335        | 81.0  | 59778 | 0.2142          | 0.1095 |
| 0.0333        | 82.0  | 60516 | 0.2154          | 0.1096 |
| 0.0327        | 83.0  | 61254 | 0.2235          | 0.1082 |
| 0.0324        | 84.0  | 61992 | 0.2192          | 0.1087 |
| 0.0319        | 85.0  | 62730 | 0.2221          | 0.1075 |
| 0.0309        | 86.0  | 63468 | 0.2210          | 0.1083 |
| 0.0309        | 87.0  | 64206 | 0.2211          | 0.1080 |
| 0.0307        | 88.0  | 64944 | 0.2226          | 0.1075 |
| 0.0297        | 89.0  | 65682 | 0.2259          | 0.1065 |
| 0.0292        | 90.0  | 66420 | 0.2242          | 0.1070 |
| 0.0291        | 91.0  | 67158 | 0.2233          | 0.1066 |
| 0.0288        | 92.0  | 67896 | 0.2287          | 0.1067 |
| 0.0283        | 93.0  | 68634 | 0.2288          | 0.1068 |
| 0.0283        | 94.0  | 69372 | 0.2269          | 0.1061 |
| 0.0279        | 95.0  | 70110 | 0.2272          | 0.1065 |
| 0.0276        | 96.0  | 70848 | 0.2290          | 0.1064 |
| 0.0273        | 97.0  | 71586 | 0.2284          | 0.1061 |
| 0.0274        | 98.0  | 72324 | 0.2272          | 0.1059 |
| 0.0272        | 99.0  | 73062 | 0.2276          | 0.1056 |
| 0.0268        | 100.0 | 73800 | 0.2280          | 0.1054 |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
