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-1_NEW
  results: []
---

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# xls-r-300m-model-1_NEW

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: 0.0024
- Wer: 0.1630
- Cer: 0.0416

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 29.2334       | 1.0   | 47   | 15.0050         | 1.0    | 1.0    |
| 9.4438        | 2.0   | 94   | 4.0843          | 1.0    | 1.0    |
| 3.6591        | 3.0   | 141  | 3.1691          | 1.0    | 1.0    |
| 3.1767        | 4.0   | 188  | 3.1468          | 1.0    | 1.0    |
| 3.1669        | 5.0   | 235  | 3.1420          | 1.0    | 1.0    |
| 3.173         | 6.0   | 282  | 3.0161          | 1.0    | 1.0    |
| 2.9708        | 7.0   | 329  | 2.8614          | 1.0    | 1.0    |
| 2.8228        | 8.0   | 376  | 2.8736          | 1.0    | 1.0    |
| 2.6826        | 9.0   | 423  | 2.4797          | 1.0    | 0.9697 |
| 2.461         | 10.0  | 470  | 2.1226          | 1.0    | 0.9365 |
| 1.9205        | 11.0  | 517  | 1.4120          | 1.0    | 0.8236 |
| 1.3314        | 12.0  | 564  | 1.0121          | 1.0    | 0.5688 |
| 0.9524        | 13.0  | 611  | 0.5546          | 0.9969 | 0.4305 |
| 0.6561        | 14.0  | 658  | 0.3299          | 0.7241 | 0.1927 |
| 0.5809        | 15.0  | 705  | 0.2833          | 0.5329 | 0.1454 |
| 0.3833        | 16.0  | 752  | 0.1045          | 0.2288 | 0.0600 |
| 0.3026        | 17.0  | 799  | 0.1345          | 0.1975 | 0.0515 |
| 0.215         | 18.0  | 846  | 0.0719          | 0.0909 | 0.0360 |
| 0.2002        | 19.0  | 893  | 0.1058          | 0.0815 | 0.0296 |
| 0.2244        | 20.0  | 940  | 0.1058          | 0.1975 | 0.0910 |
| 0.1574        | 21.0  | 987  | 0.1111          | 0.1661 | 0.0614 |
| 0.1632        | 22.0  | 1034 | 0.0619          | 0.1348 | 0.0438 |
| 0.1399        | 23.0  | 1081 | 0.0577          | 0.0909 | 0.0191 |
| 0.1747        | 24.0  | 1128 | 0.0411          | 0.0846 | 0.0205 |
| 0.129         | 25.0  | 1175 | 0.0320          | 0.0564 | 0.0127 |
| 0.14          | 26.0  | 1222 | 0.0580          | 0.0470 | 0.0141 |
| 0.1135        | 27.0  | 1269 | 0.0482          | 0.0282 | 0.0085 |
| 0.1172        | 28.0  | 1316 | 0.0829          | 0.0596 | 0.0198 |
| 0.0736        | 29.0  | 1363 | 0.0688          | 0.0972 | 0.0318 |
| 0.0693        | 30.0  | 1410 | 0.0207          | 0.0815 | 0.0191 |
| 0.0862        | 31.0  | 1457 | 0.0106          | 0.0157 | 0.0035 |
| 0.0788        | 32.0  | 1504 | 0.0095          | 0.0909 | 0.0205 |
| 0.0524        | 33.0  | 1551 | 0.0102          | 0.1003 | 0.0240 |
| 0.062         | 34.0  | 1598 | 0.0331          | 0.1097 | 0.0275 |
| 0.0646        | 35.0  | 1645 | 0.0188          | 0.0909 | 0.0254 |
| 0.0793        | 36.0  | 1692 | 0.0148          | 0.1066 | 0.0261 |
| 0.0607        | 37.0  | 1739 | 0.0135          | 0.1379 | 0.0395 |
| 0.0417        | 38.0  | 1786 | 0.0209          | 0.1379 | 0.0360 |
| 0.0559        | 39.0  | 1833 | 0.0216          | 0.1599 | 0.0388 |
| 0.0668        | 40.0  | 1880 | 0.0136          | 0.1066 | 0.0275 |
| 0.0501        | 41.0  | 1927 | 0.0218          | 0.0940 | 0.0233 |
| 0.0397        | 42.0  | 1974 | 0.0065          | 0.1066 | 0.0261 |
| 0.0379        | 43.0  | 2021 | 0.0053          | 0.0784 | 0.0183 |
| 0.041         | 44.0  | 2068 | 0.0018          | 0.1411 | 0.0339 |
| 0.0265        | 45.0  | 2115 | 0.0065          | 0.1505 | 0.0346 |
| 0.0316        | 46.0  | 2162 | 0.0067          | 0.0721 | 0.0169 |
| 0.0401        | 47.0  | 2209 | 0.0169          | 0.1003 | 0.0275 |
| 0.0435        | 48.0  | 2256 | 0.0119          | 0.1129 | 0.0275 |
| 0.0287        | 49.0  | 2303 | 0.0108          | 0.1097 | 0.0254 |
| 0.0416        | 50.0  | 2350 | 0.0060          | 0.1348 | 0.0311 |
| 0.0295        | 51.0  | 2397 | 0.0078          | 0.1442 | 0.0332 |
| 0.0269        | 52.0  | 2444 | 0.0050          | 0.1285 | 0.0296 |
| 0.0285        | 53.0  | 2491 | 0.0044          | 0.1411 | 0.0332 |
| 0.0364        | 54.0  | 2538 | 0.0016          | 0.1473 | 0.0332 |
| 0.03          | 55.0  | 2585 | 0.0026          | 0.1536 | 0.0388 |
| 0.0218        | 56.0  | 2632 | 0.0032          | 0.1599 | 0.0423 |
| 0.0183        | 57.0  | 2679 | 0.0022          | 0.1630 | 0.0416 |
| 0.0238        | 58.0  | 2726 | 0.0018          | 0.1661 | 0.0416 |
| 0.0232        | 59.0  | 2773 | 0.0026          | 0.1661 | 0.0423 |
| 0.0174        | 60.0  | 2820 | 0.0024          | 0.1630 | 0.0416 |


### Framework versions

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