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-D
  results: []
---

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# xls-r-300m-model-D

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: 1.7217
- Wer: 0.9969
- Cer: 0.6902

## 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: 2e-05
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 32.0223       | 1.0   | 47   | 31.7006         | 1.0    | 2.6627 |
| 30.6191       | 2.0   | 94   | 28.7189         | 1.0    | 0.9802 |
| 23.48         | 3.0   | 141  | 14.8504         | 1.0    | 1.0    |
| 13.7384       | 4.0   | 188  | 8.6016          | 1.0    | 1.0    |
| 9.6022        | 5.0   | 235  | 6.3337          | 1.0    | 1.0    |
| 7.0718        | 6.0   | 282  | 5.0846          | 1.0    | 1.0    |
| 5.3429        | 7.0   | 329  | 4.2855          | 1.0    | 1.0    |
| 4.3829        | 8.0   | 376  | 3.8110          | 1.0    | 1.0    |
| 3.9108        | 9.0   | 423  | 3.5171          | 1.0    | 1.0    |
| 3.5356        | 10.0  | 470  | 3.3415          | 1.0    | 1.0    |
| 3.3748        | 11.0  | 517  | 3.2509          | 1.0    | 1.0    |
| 3.2788        | 12.0  | 564  | 3.2040          | 1.0    | 1.0    |
| 3.2254        | 13.0  | 611  | 3.1804          | 1.0    | 1.0    |
| 3.1871        | 14.0  | 658  | 3.1688          | 1.0    | 1.0    |
| 3.1704        | 15.0  | 705  | 3.1607          | 1.0    | 1.0    |
| 3.1741        | 16.0  | 752  | 3.1564          | 1.0    | 1.0    |
| 3.1516        | 17.0  | 799  | 3.1502          | 1.0    | 1.0    |
| 3.1504        | 18.0  | 846  | 3.1475          | 1.0    | 1.0    |
| 3.1475        | 19.0  | 893  | 3.1443          | 1.0    | 1.0    |
| 3.1404        | 20.0  | 940  | 3.1384          | 1.0    | 1.0    |
| 3.1413        | 21.0  | 987  | 3.1333          | 1.0    | 1.0    |
| 3.1307        | 22.0  | 1034 | 3.1230          | 1.0    | 1.0    |
| 3.1252        | 23.0  | 1081 | 3.0888          | 1.0    | 1.0    |
| 3.1063        | 24.0  | 1128 | 3.0454          | 1.0    | 1.0    |
| 3.0689        | 25.0  | 1175 | 2.9970          | 1.0    | 1.0    |
| 3.0212        | 26.0  | 1222 | 2.9566          | 1.0    | 1.0    |
| 2.9718        | 27.0  | 1269 | 2.8838          | 1.0    | 1.0    |
| 2.9241        | 28.0  | 1316 | 2.8342          | 1.0    | 1.0    |
| 2.874         | 29.0  | 1363 | 2.7721          | 1.0    | 0.9492 |
| 2.8058        | 30.0  | 1410 | 2.7171          | 1.0    | 0.9005 |
| 2.7639        | 31.0  | 1457 | 2.6737          | 1.0    | 0.8525 |
| 2.7273        | 32.0  | 1504 | 2.6319          | 1.0    | 0.8546 |
| 2.6737        | 33.0  | 1551 | 2.5578          | 1.0    | 0.8440 |
| 2.6197        | 34.0  | 1598 | 2.5156          | 1.0    | 0.8391 |
| 2.5877        | 35.0  | 1645 | 2.4513          | 1.0    | 0.8335 |
| 2.5275        | 36.0  | 1692 | 2.3993          | 1.0    | 0.8405 |
| 2.4871        | 37.0  | 1739 | 2.3387          | 1.0    | 0.8292 |
| 2.4367        | 38.0  | 1786 | 2.2844          | 1.0    | 0.8384 |
| 2.3918        | 39.0  | 1833 | 2.2465          | 1.0    | 0.8342 |
| 2.3633        | 40.0  | 1880 | 2.1934          | 1.0    | 0.8215 |
| 2.3201        | 41.0  | 1927 | 2.1387          | 1.0    | 0.8215 |
| 2.2691        | 42.0  | 1974 | 2.1210          | 1.0    | 0.8158 |
| 2.2387        | 43.0  | 2021 | 2.0740          | 1.0    | 0.8073 |
| 2.195         | 44.0  | 2068 | 2.0135          | 1.0    | 0.7939 |
| 2.1438        | 45.0  | 2115 | 1.9877          | 1.0    | 0.7855 |
| 2.1288        | 46.0  | 2162 | 1.9605          | 0.9969 | 0.7530 |
| 2.1215        | 47.0  | 2209 | 1.9264          | 0.9969 | 0.7481 |
| 2.0892        | 48.0  | 2256 | 1.8813          | 1.0    | 0.7318 |
| 2.0759        | 49.0  | 2303 | 1.8614          | 1.0    | 0.7255 |
| 2.0326        | 50.0  | 2350 | 1.8368          | 1.0    | 0.7198 |
| 2.0058        | 51.0  | 2397 | 1.8204          | 0.9969 | 0.7121 |
| 2.0022        | 52.0  | 2444 | 1.7939          | 1.0    | 0.7022 |
| 2.0073        | 53.0  | 2491 | 1.7808          | 0.9969 | 0.7036 |
| 1.9757        | 54.0  | 2538 | 1.7677          | 1.0    | 0.7001 |
| 1.9783        | 55.0  | 2585 | 1.7468          | 1.0    | 0.6958 |
| 1.9394        | 56.0  | 2632 | 1.7406          | 1.0    | 0.6958 |
| 1.9373        | 57.0  | 2679 | 1.7265          | 0.9969 | 0.6923 |
| 1.936         | 58.0  | 2726 | 1.7197          | 0.9969 | 0.6888 |
| 1.9291        | 59.0  | 2773 | 1.7206          | 0.9969 | 0.6916 |
| 1.9272        | 60.0  | 2820 | 1.7217          | 0.9969 | 0.6902 |


### Framework versions

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