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-4
  results: []
---

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# xls-r-300m-model-4

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: 0.1161
- Wer: 0.2163
- Cer: 0.0593

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 27.7684       | 1.0   | 47   | 14.3947         | 1.0    | 1.0    |
| 9.0101        | 2.0   | 94   | 4.2287          | 1.0    | 1.0    |
| 3.5959        | 3.0   | 141  | 3.1880          | 1.0    | 1.0    |
| 3.1801        | 4.0   | 188  | 3.1428          | 1.0    | 1.0    |
| 3.1508        | 5.0   | 235  | 3.0521          | 1.0    | 1.0    |
| 2.967         | 6.0   | 282  | 2.9580          | 1.0    | 1.0    |
| 2.7746        | 7.0   | 329  | 2.5700          | 1.0    | 1.0    |
| 2.449         | 8.0   | 376  | 2.0616          | 1.0    | 0.9358 |
| 1.6959        | 9.0   | 423  | 1.2861          | 1.0    | 0.6803 |
| 1.0742        | 10.0  | 470  | 0.7718          | 0.9937 | 0.4192 |
| 0.7025        | 11.0  | 517  | 0.4683          | 0.8025 | 0.2900 |
| 0.4039        | 12.0  | 564  | 0.3167          | 0.5298 | 0.2258 |
| 0.2477        | 13.0  | 611  | 0.2589          | 0.3793 | 0.1306 |
| 0.2605        | 14.0  | 658  | 0.2206          | 0.3918 | 0.1291 |
| 0.1525        | 15.0  | 705  | 0.2110          | 0.4013 | 0.1186 |
| 0.2108        | 16.0  | 752  | 0.1722          | 0.4107 | 0.1447 |
| 0.1358        | 17.0  | 799  | 0.1396          | 0.2978 | 0.0953 |
| 0.0716        | 18.0  | 846  | 0.1844          | 0.3511 | 0.0932 |
| 0.0567        | 19.0  | 893  | 0.1037          | 0.2602 | 0.0727 |
| 0.0675        | 20.0  | 940  | 0.0943          | 0.2382 | 0.0713 |
| 0.0651        | 21.0  | 987  | 0.1244          | 0.2539 | 0.0939 |
| 0.0893        | 22.0  | 1034 | 0.1289          | 0.2884 | 0.0967 |
| 0.0925        | 23.0  | 1081 | 0.1417          | 0.3229 | 0.1355 |
| 0.0659        | 24.0  | 1128 | 0.1326          | 0.3103 | 0.1313 |
| 0.0582        | 25.0  | 1175 | 0.0892          | 0.2821 | 0.1355 |
| 0.0526        | 26.0  | 1222 | 0.1754          | 0.2978 | 0.0797 |
| 0.0797        | 27.0  | 1269 | 0.1246          | 0.2602 | 0.0734 |
| 0.0366        | 28.0  | 1316 | 0.0984          | 0.2759 | 0.0875 |
| 0.0288        | 29.0  | 1363 | 0.0707          | 0.2257 | 0.0656 |
| 0.018         | 30.0  | 1410 | 0.0824          | 0.2257 | 0.0670 |
| 0.0329        | 31.0  | 1457 | 0.0924          | 0.2288 | 0.0748 |
| 0.0336        | 32.0  | 1504 | 0.1281          | 0.2539 | 0.0882 |
| 0.0299        | 33.0  | 1551 | 0.1219          | 0.2257 | 0.0593 |
| 0.0304        | 34.0  | 1598 | 0.1435          | 0.2351 | 0.0642 |
| 0.0732        | 35.0  | 1645 | 0.1605          | 0.2320 | 0.0734 |
| 0.0691        | 36.0  | 1692 | 0.0925          | 0.2132 | 0.0572 |
| 0.0284        | 37.0  | 1739 | 0.0951          | 0.2320 | 0.0692 |
| 0.0374        | 38.0  | 1786 | 0.0844          | 0.1881 | 0.0529 |
| 0.034         | 39.0  | 1833 | 0.0757          | 0.2351 | 0.0670 |
| 0.0172        | 40.0  | 1880 | 0.0632          | 0.2351 | 0.0642 |
| 0.0343        | 41.0  | 1927 | 0.1404          | 0.2288 | 0.0692 |
| 0.0424        | 42.0  | 1974 | 0.1433          | 0.2476 | 0.0762 |
| 0.0235        | 43.0  | 2021 | 0.1542          | 0.2571 | 0.1009 |
| 0.0219        | 44.0  | 2068 | 0.1100          | 0.2476 | 0.0819 |
| 0.0281        | 45.0  | 2115 | 0.1478          | 0.2320 | 0.0677 |
| 0.0205        | 46.0  | 2162 | 0.0797          | 0.2288 | 0.0706 |
| 0.0271        | 47.0  | 2209 | 0.1139          | 0.2382 | 0.0734 |
| 0.0288        | 48.0  | 2256 | 0.1264          | 0.2226 | 0.0670 |
| 0.0141        | 49.0  | 2303 | 0.1322          | 0.2288 | 0.0692 |
| 0.008         | 50.0  | 2350 | 0.1226          | 0.2226 | 0.0614 |
| 0.0098        | 51.0  | 2397 | 0.1146          | 0.1975 | 0.0621 |
| 0.006         | 52.0  | 2444 | 0.1116          | 0.2100 | 0.0635 |
| 0.0109        | 53.0  | 2491 | 0.1087          | 0.2163 | 0.0621 |
| 0.0058        | 54.0  | 2538 | 0.1176          | 0.2069 | 0.0565 |
| 0.0095        | 55.0  | 2585 | 0.1178          | 0.2132 | 0.0572 |
| 0.0061        | 56.0  | 2632 | 0.1193          | 0.2194 | 0.0579 |
| 0.011         | 57.0  | 2679 | 0.1152          | 0.2163 | 0.0579 |
| 0.0033        | 58.0  | 2726 | 0.1152          | 0.2163 | 0.0593 |
| 0.0045        | 59.0  | 2773 | 0.1160          | 0.2163 | 0.0586 |
| 0.0072        | 60.0  | 2820 | 0.1161          | 0.2163 | 0.0593 |


### Framework versions

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