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-F
  results: []
---

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# xls-r-300m-model-F

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: 2.4769
- Wer: 1.0
- Cer: 0.8567

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:---:|:------:|
| 32.1153       | 1.0   | 47   | 31.9339         | 1.0 | 1.9217 |
| 31.0227       | 2.0   | 94   | 30.0595         | 1.0 | 1.1023 |
| 26.5289       | 3.0   | 141  | 22.8137         | 1.0 | 1.0    |
| 16.2501       | 4.0   | 188  | 10.2118         | 1.0 | 1.0    |
| 10.5699       | 5.0   | 235  | 6.5570          | 1.0 | 1.0    |
| 7.3764        | 6.0   | 282  | 5.0657          | 1.0 | 1.0    |
| 5.3976        | 7.0   | 329  | 4.1925          | 1.0 | 1.0    |
| 4.3718        | 8.0   | 376  | 3.7204          | 1.0 | 1.0    |
| 3.8762        | 9.0   | 423  | 3.4513          | 1.0 | 1.0    |
| 3.5061        | 10.0  | 470  | 3.2995          | 1.0 | 1.0    |
| 3.3488        | 11.0  | 517  | 3.2259          | 1.0 | 1.0    |
| 3.2622        | 12.0  | 564  | 3.1920          | 1.0 | 1.0    |
| 3.2165        | 13.0  | 611  | 3.1745          | 1.0 | 1.0    |
| 3.18          | 14.0  | 658  | 3.1655          | 1.0 | 1.0    |
| 3.1688        | 15.0  | 705  | 3.1578          | 1.0 | 1.0    |
| 3.172         | 16.0  | 752  | 3.1574          | 1.0 | 1.0    |
| 3.1514        | 17.0  | 799  | 3.1510          | 1.0 | 1.0    |
| 3.1505        | 18.0  | 846  | 3.1493          | 1.0 | 1.0    |
| 3.148         | 19.0  | 893  | 3.1484          | 1.0 | 1.0    |
| 3.1424        | 20.0  | 940  | 3.1446          | 1.0 | 1.0    |
| 3.1448        | 21.0  | 987  | 3.1420          | 1.0 | 1.0    |
| 3.139         | 22.0  | 1034 | 3.1400          | 1.0 | 1.0    |
| 3.1408        | 23.0  | 1081 | 3.1358          | 1.0 | 1.0    |
| 3.1357        | 24.0  | 1128 | 3.1326          | 1.0 | 1.0    |
| 3.1322        | 25.0  | 1175 | 3.1284          | 1.0 | 1.0    |
| 3.1246        | 26.0  | 1222 | 3.1256          | 1.0 | 1.0    |
| 3.1294        | 27.0  | 1269 | 3.1162          | 1.0 | 1.0    |
| 3.1238        | 28.0  | 1316 | 3.1045          | 1.0 | 1.0    |
| 3.1183        | 29.0  | 1363 | 3.0778          | 1.0 | 1.0    |
| 3.0784        | 30.0  | 1410 | 3.1226          | 1.0 | 1.0    |
| 3.0611        | 31.0  | 1457 | 3.0231          | 1.0 | 1.0    |
| 3.0356        | 32.0  | 1504 | 3.0102          | 1.0 | 1.0    |
| 3.0014        | 33.0  | 1551 | 2.9689          | 1.0 | 1.0    |
| 2.9721        | 34.0  | 1598 | 2.9379          | 1.0 | 1.0    |
| 2.9472        | 35.0  | 1645 | 2.8771          | 1.0 | 1.0    |
| 2.9201        | 36.0  | 1692 | 2.8427          | 1.0 | 1.0    |
| 2.8779        | 37.0  | 1739 | 2.8147          | 1.0 | 1.0    |
| 2.8452        | 38.0  | 1786 | 2.7851          | 1.0 | 1.0    |
| 2.8276        | 39.0  | 1833 | 2.7496          | 1.0 | 0.9922 |
| 2.8059        | 40.0  | 1880 | 2.7214          | 1.0 | 0.9647 |
| 2.783         | 41.0  | 1927 | 2.6950          | 1.0 | 0.9273 |
| 2.7501        | 42.0  | 1974 | 2.6865          | 1.0 | 0.9097 |
| 2.7372        | 43.0  | 2021 | 2.6548          | 1.0 | 0.9125 |
| 2.7148        | 44.0  | 2068 | 2.6345          | 1.0 | 0.9083 |
| 2.687         | 45.0  | 2115 | 2.6206          | 1.0 | 0.8878 |
| 2.6763        | 46.0  | 2162 | 2.5913          | 1.0 | 0.8920 |
| 2.6653        | 47.0  | 2209 | 2.5812          | 1.0 | 0.8730 |
| 2.6526        | 48.0  | 2256 | 2.5677          | 1.0 | 0.8701 |
| 2.6442        | 49.0  | 2303 | 2.5460          | 1.0 | 0.8645 |
| 2.6226        | 50.0  | 2350 | 2.5414          | 1.0 | 0.8589 |
| 2.6065        | 51.0  | 2397 | 2.5251          | 1.0 | 0.8659 |
| 2.5939        | 52.0  | 2444 | 2.5120          | 1.0 | 0.8631 |
| 2.5973        | 53.0  | 2491 | 2.5066          | 1.0 | 0.8589 |
| 2.5888        | 54.0  | 2538 | 2.4987          | 1.0 | 0.8567 |
| 2.5878        | 55.0  | 2585 | 2.4962          | 1.0 | 0.8560 |
| 2.5608        | 56.0  | 2632 | 2.4851          | 1.0 | 0.8574 |
| 2.5687        | 57.0  | 2679 | 2.4839          | 1.0 | 0.8567 |
| 2.5594        | 58.0  | 2726 | 2.4864          | 1.0 | 0.8589 |
| 2.557         | 59.0  | 2773 | 2.4757          | 1.0 | 0.8567 |
| 2.5553        | 60.0  | 2820 | 2.4769          | 1.0 | 0.8567 |


### Framework versions

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