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-2
  results: []
---

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# xls-r-300m-model-2

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: 0.0100
- Wer: 0.1630
- Cer: 0.0543

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.3091       | 1.0   | 47   | 12.5816         | 1.0    | 1.0    |
| 8.1185        | 2.0   | 94   | 4.0610          | 1.0    | 1.0    |
| 3.5739        | 3.0   | 141  | 3.1872          | 1.0    | 1.0    |
| 3.1895        | 4.0   | 188  | 3.1399          | 1.0    | 1.0    |
| 3.1433        | 5.0   | 235  | 3.0083          | 1.0    | 1.0    |
| 3.01          | 6.0   | 282  | 2.8420          | 1.0    | 1.0    |
| 2.7873        | 7.0   | 329  | 2.7332          | 1.0    | 0.9802 |
| 2.6089        | 8.0   | 376  | 2.4772          | 1.0    | 0.8920 |
| 2.1861        | 9.0   | 423  | 1.9047          | 1.0    | 0.7375 |
| 1.8622        | 10.0  | 470  | 1.3076          | 1.0    | 0.6528 |
| 1.2815        | 11.0  | 517  | 0.9163          | 1.0    | 0.4975 |
| 1.0227        | 12.0  | 564  | 0.7301          | 0.9655 | 0.4100 |
| 0.7393        | 13.0  | 611  | 0.5188          | 0.8025 | 0.4622 |
| 0.5328        | 14.0  | 658  | 0.2949          | 0.6301 | 0.2661 |
| 0.3925        | 15.0  | 705  | 0.2821          | 0.4389 | 0.1348 |
| 0.3234        | 16.0  | 752  | 0.2217          | 0.3668 | 0.1066 |
| 0.3948        | 17.0  | 799  | 0.1686          | 0.2978 | 0.0995 |
| 0.2397        | 18.0  | 846  | 0.1839          | 0.2633 | 0.0910 |
| 0.1977        | 19.0  | 893  | 0.0884          | 0.2257 | 0.0593 |
| 0.2011        | 20.0  | 940  | 0.0583          | 0.1034 | 0.0247 |
| 0.1835        | 21.0  | 987  | 0.1113          | 0.1755 | 0.0487 |
| 0.132         | 22.0  | 1034 | 0.0680          | 0.0878 | 0.0219 |
| 0.1707        | 23.0  | 1081 | 0.0788          | 0.1755 | 0.0452 |
| 0.1541        | 24.0  | 1128 | 0.0246          | 0.0470 | 0.0106 |
| 0.085         | 25.0  | 1175 | 0.0224          | 0.0690 | 0.0155 |
| 0.2138        | 26.0  | 1222 | 0.0681          | 0.0878 | 0.0226 |
| 0.1498        | 27.0  | 1269 | 0.0211          | 0.0752 | 0.0183 |
| 0.1187        | 28.0  | 1316 | 0.0534          | 0.0596 | 0.0155 |
| 0.1166        | 29.0  | 1363 | 0.0388          | 0.0690 | 0.0176 |
| 0.1027        | 30.0  | 1410 | 0.0291          | 0.0502 | 0.0127 |
| 0.0588        | 31.0  | 1457 | 0.0534          | 0.1254 | 0.0311 |
| 0.0659        | 32.0  | 1504 | 0.0383          | 0.1317 | 0.0332 |
| 0.0736        | 33.0  | 1551 | 0.0396          | 0.1411 | 0.0339 |
| 0.0682        | 34.0  | 1598 | 0.0720          | 0.2539 | 0.0677 |
| 0.0793        | 35.0  | 1645 | 0.1239          | 0.2476 | 0.0882 |
| 0.0464        | 36.0  | 1692 | 0.0637          | 0.2571 | 0.1080 |
| 0.0453        | 37.0  | 1739 | 0.0229          | 0.2257 | 0.0776 |
| 0.0425        | 38.0  | 1786 | 0.0178          | 0.1787 | 0.0487 |
| 0.0792        | 39.0  | 1833 | 0.0739          | 0.1724 | 0.0593 |
| 0.063         | 40.0  | 1880 | 0.0274          | 0.1442 | 0.0473 |
| 0.0475        | 41.0  | 1927 | 0.0201          | 0.0940 | 0.0282 |
| 0.0471        | 42.0  | 1974 | 0.0155          | 0.0846 | 0.0219 |
| 0.0532        | 43.0  | 2021 | 0.1041          | 0.1411 | 0.0466 |
| 0.0485        | 44.0  | 2068 | 0.1166          | 0.1160 | 0.0318 |
| 0.0333        | 45.0  | 2115 | 0.0133          | 0.1317 | 0.0311 |
| 0.0314        | 46.0  | 2162 | 0.0115          | 0.1411 | 0.0367 |
| 0.0328        | 47.0  | 2209 | 0.0245          | 0.1599 | 0.0423 |
| 0.0315        | 48.0  | 2256 | 0.0172          | 0.1724 | 0.0395 |
| 0.0337        | 49.0  | 2303 | 0.0126          | 0.1034 | 0.0247 |
| 0.0187        | 50.0  | 2350 | 0.0109          | 0.1066 | 0.0240 |
| 0.0209        | 51.0  | 2397 | 0.0118          | 0.1536 | 0.0430 |
| 0.0158        | 52.0  | 2444 | 0.0122          | 0.1599 | 0.0522 |
| 0.028         | 53.0  | 2491 | 0.0092          | 0.1630 | 0.0508 |
| 0.024         | 54.0  | 2538 | 0.0091          | 0.1473 | 0.0459 |
| 0.0191        | 55.0  | 2585 | 0.0095          | 0.1473 | 0.0473 |
| 0.0155        | 56.0  | 2632 | 0.0100          | 0.1473 | 0.0466 |
| 0.0219        | 57.0  | 2679 | 0.0098          | 0.1567 | 0.0515 |
| 0.0156        | 58.0  | 2726 | 0.0099          | 0.1661 | 0.0543 |
| 0.0149        | 59.0  | 2773 | 0.0100          | 0.1693 | 0.0558 |
| 0.0169        | 60.0  | 2820 | 0.0100          | 0.1630 | 0.0543 |


### Framework versions

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