transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-300m-model-3
  results: []
---

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# xls-r-300m-model-3

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: 0.0588
- Wer: 0.3824
- Cer: 0.1108

## 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: 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_ratio: 0.1
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.5714       | 1.0   | 47   | 14.0582         | 1.0    | 1.0    |
| 9.1376        | 2.0   | 94   | 3.9617          | 1.0    | 1.0    |
| 3.5313        | 3.0   | 141  | 3.1685          | 1.0    | 1.0    |
| 3.1824        | 4.0   | 188  | 3.1454          | 1.0    | 1.0    |
| 3.1515        | 5.0   | 235  | 3.2191          | 1.0    | 1.0    |
| 3.1334        | 6.0   | 282  | 3.0060          | 1.0    | 1.0    |
| 2.9592        | 7.0   | 329  | 2.8529          | 1.0    | 1.0    |
| 2.8578        | 8.0   | 376  | 2.6646          | 1.0    | 1.0    |
| 2.7037        | 9.0   | 423  | 2.5452          | 1.0    | 0.9781 |
| 2.4728        | 10.0  | 470  | 2.2896          | 1.0    | 0.8737 |
| 2.0318        | 11.0  | 517  | 1.5268          | 1.0    | 0.6782 |
| 1.39          | 12.0  | 564  | 1.0841          | 1.0    | 0.4622 |
| 0.8994        | 13.0  | 611  | 0.5316          | 1.0    | 0.3691 |
| 0.6888        | 14.0  | 658  | 0.5907          | 0.9498 | 0.2576 |
| 0.4924        | 15.0  | 705  | 0.3629          | 0.9154 | 0.2548 |
| 0.4083        | 16.0  | 752  | 0.2853          | 0.7774 | 0.2421 |
| 0.3278        | 17.0  | 799  | 0.1644          | 0.7524 | 0.2174 |
| 0.2391        | 18.0  | 846  | 0.1845          | 0.6082 | 0.1771 |
| 0.2025        | 19.0  | 893  | 0.1324          | 0.5549 | 0.1334 |
| 0.2015        | 20.0  | 940  | 0.2035          | 0.5361 | 0.1658 |
| 0.1966        | 21.0  | 987  | 0.1196          | 0.5392 | 0.1313 |
| 0.2209        | 22.0  | 1034 | 0.1193          | 0.5078 | 0.1009 |
| 0.1588        | 23.0  | 1081 | 0.0958          | 0.5862 | 0.2040 |
| 0.1134        | 24.0  | 1128 | 0.1008          | 0.5455 | 0.1376 |
| 0.1106        | 25.0  | 1175 | 0.0783          | 0.4734 | 0.1503 |
| 0.1249        | 26.0  | 1222 | 0.0652          | 0.4138 | 0.0854 |
| 0.0797        | 27.0  | 1269 | 0.1045          | 0.4734 | 0.1284 |
| 0.1123        | 28.0  | 1316 | 0.1391          | 0.4389 | 0.1052 |
| 0.0916        | 29.0  | 1363 | 0.0699          | 0.4138 | 0.1023 |
| 0.0718        | 30.0  | 1410 | 0.0789          | 0.3762 | 0.0847 |
| 0.0927        | 31.0  | 1457 | 0.0839          | 0.4577 | 0.1179 |
| 0.1101        | 32.0  | 1504 | 0.1126          | 0.4138 | 0.1052 |
| 0.0718        | 33.0  | 1551 | 0.0711          | 0.4263 | 0.1066 |
| 0.067         | 34.0  | 1598 | 0.1456          | 0.4263 | 0.1200 |
| 0.0727        | 35.0  | 1645 | 0.1152          | 0.4138 | 0.1228 |
| 0.045         | 36.0  | 1692 | 0.1489          | 0.4295 | 0.1355 |
| 0.0607        | 37.0  | 1739 | 0.0833          | 0.3762 | 0.0812 |
| 0.0465        | 38.0  | 1786 | 0.1160          | 0.4075 | 0.1235 |
| 0.0564        | 39.0  | 1833 | 0.1005          | 0.4169 | 0.1277 |
| 0.05          | 40.0  | 1880 | 0.0842          | 0.4107 | 0.1454 |
| 0.033         | 41.0  | 1927 | 0.0838          | 0.3856 | 0.1164 |
| 0.0329        | 42.0  | 1974 | 0.0968          | 0.4075 | 0.1482 |
| 0.0353        | 43.0  | 2021 | 0.0992          | 0.3887 | 0.1023 |
| 0.0371        | 44.0  | 2068 | 0.1162          | 0.3981 | 0.1362 |
| 0.0285        | 45.0  | 2115 | 0.0999          | 0.3950 | 0.1362 |
| 0.0324        | 46.0  | 2162 | 0.0875          | 0.3918 | 0.1348 |
| 0.0305        | 47.0  | 2209 | 0.0789          | 0.4044 | 0.1560 |
| 0.0292        | 48.0  | 2256 | 0.0772          | 0.3981 | 0.1496 |
| 0.0225        | 49.0  | 2303 | 0.0767          | 0.3950 | 0.1553 |
| 0.0271        | 50.0  | 2350 | 0.0892          | 0.3950 | 0.1136 |
| 0.0231        | 51.0  | 2397 | 0.0905          | 0.3824 | 0.1023 |
| 0.0198        | 52.0  | 2444 | 0.0908          | 0.3793 | 0.1044 |
| 0.0263        | 53.0  | 2491 | 0.0750          | 0.3824 | 0.1023 |
| 0.022         | 54.0  | 2538 | 0.0666          | 0.3793 | 0.1016 |
| 0.0235        | 55.0  | 2585 | 0.0621          | 0.3762 | 0.0995 |
| 0.0267        | 56.0  | 2632 | 0.0563          | 0.3824 | 0.1073 |
| 0.0379        | 57.0  | 2679 | 0.0578          | 0.3856 | 0.1108 |
| 0.0243        | 58.0  | 2726 | 0.0596          | 0.3856 | 0.1115 |
| 0.0261        | 59.0  | 2773 | 0.0587          | 0.3824 | 0.1094 |
| 0.0249        | 60.0  | 2820 | 0.0588          | 0.3824 | 0.1108 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3
