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-A
  results: []
---

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# xls-r-300m-model-A

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: 0.3617
- Wer: 0.3417
- Cer: 0.3359

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 26.6792       | 1.0   | 47   | 10.9107         | 1.0    | 1.0    |
| 7.8048        | 2.0   | 94   | 3.6963          | 1.0    | 1.0    |
| 3.4503        | 3.0   | 141  | 3.1623          | 1.0    | 1.0    |
| 3.1703        | 4.0   | 188  | 3.1486          | 1.0    | 1.0    |
| 3.1754        | 5.0   | 235  | 3.1398          | 1.0    | 1.0    |
| 3.19          | 6.0   | 282  | 3.1649          | 1.0    | 1.0    |
| 3.0893        | 7.0   | 329  | 3.1219          | 1.0    | 1.0    |
| 2.9698        | 8.0   | 376  | 2.8057          | 1.0    | 1.0    |
| 2.8622        | 9.0   | 423  | 2.7599          | 1.0    | 1.0    |
| 2.7293        | 10.0  | 470  | 2.5735          | 1.0    | 0.8694 |
| 2.6369        | 11.0  | 517  | 2.4812          | 1.0    | 0.8518 |
| 2.4521        | 12.0  | 564  | 2.3214          | 1.0    | 0.7911 |
| 2.3405        | 13.0  | 611  | 2.1990          | 1.0    | 0.7530 |
| 2.1983        | 14.0  | 658  | 2.0527          | 1.0    | 0.7339 |
| 2.1379        | 15.0  | 705  | 2.0385          | 1.0    | 0.7283 |
| 2.0842        | 16.0  | 752  | 1.9515          | 1.0    | 0.7198 |
| 2.0469        | 17.0  | 799  | 1.9015          | 1.0    | 0.7205 |
| 1.9494        | 18.0  | 846  | 1.9291          | 1.0    | 0.7163 |
| 2.0306        | 19.0  | 893  | 1.8532          | 1.0    | 0.7092 |
| 1.8124        | 20.0  | 940  | 1.6457          | 1.0    | 0.6733 |
| 1.7114        | 21.0  | 987  | 1.4539          | 0.9561 | 0.6239 |
| 1.5781        | 22.0  | 1034 | 1.5011          | 0.9592 | 0.7368 |
| 1.486         | 23.0  | 1081 | 1.4219          | 0.9154 | 0.5801 |
| 1.3247        | 24.0  | 1128 | 1.1263          | 0.8997 | 0.5293 |
| 1.2121        | 25.0  | 1175 | 1.5609          | 0.9279 | 0.6598 |
| 1.1214        | 26.0  | 1222 | 0.9734          | 0.8966 | 0.4919 |
| 0.9949        | 27.0  | 1269 | 1.0702          | 0.8966 | 0.5159 |
| 0.905         | 28.0  | 1316 | 0.7401          | 0.8809 | 0.4263 |
| 0.8187        | 29.0  | 1363 | 0.6565          | 0.8056 | 0.3924 |
| 0.6954        | 30.0  | 1410 | 0.5022          | 0.7398 | 0.3578 |
| 0.6616        | 31.0  | 1457 | 0.4858          | 0.7085 | 0.3634 |
| 0.5332        | 32.0  | 1504 | 0.4242          | 0.6207 | 0.2844 |
| 0.5323        | 33.0  | 1551 | 0.3704          | 0.5705 | 0.2583 |
| 0.4133        | 34.0  | 1598 | 0.3560          | 0.5831 | 0.2682 |
| 0.4121        | 35.0  | 1645 | 0.3449          | 0.5517 | 0.2696 |
| 0.4243        | 36.0  | 1692 | 0.4157          | 0.5517 | 0.2802 |
| 0.3316        | 37.0  | 1739 | 0.4054          | 0.5611 | 0.3507 |
| 0.2774        | 38.0  | 1786 | 0.4340          | 0.5517 | 0.3606 |
| 0.3415        | 39.0  | 1833 | 0.3619          | 0.5298 | 0.3409 |
| 0.2722        | 40.0  | 1880 | 0.3098          | 0.4232 | 0.3705 |
| 0.2532        | 41.0  | 1927 | 0.2978          | 0.3950 | 0.2569 |
| 0.173         | 42.0  | 1974 | 0.2661          | 0.3605 | 0.2167 |
| 0.2258        | 43.0  | 2021 | 0.2203          | 0.3480 | 0.2329 |
| 0.1722        | 44.0  | 2068 | 0.3302          | 0.3605 | 0.2646 |
| 0.1648        | 45.0  | 2115 | 0.2736          | 0.4107 | 0.3507 |
| 0.2142        | 46.0  | 2162 | 0.4359          | 0.3762 | 0.3366 |
| 0.1417        | 47.0  | 2209 | 0.3170          | 0.3417 | 0.3331 |
| 0.1138        | 48.0  | 2256 | 0.2937          | 0.3448 | 0.2548 |
| 0.1506        | 49.0  | 2303 | 0.3907          | 0.3636 | 0.3387 |
| 0.0958        | 50.0  | 2350 | 0.3740          | 0.3448 | 0.3020 |
| 0.1082        | 51.0  | 2397 | 0.2869          | 0.3135 | 0.2809 |
| 0.1229        | 52.0  | 2444 | 0.2933          | 0.3542 | 0.3267 |
| 0.1173        | 53.0  | 2491 | 0.3282          | 0.3480 | 0.3070 |
| 0.1222        | 54.0  | 2538 | 0.3940          | 0.3542 | 0.3458 |
| 0.0832        | 55.0  | 2585 | 0.3013          | 0.3354 | 0.3126 |
| 0.0599        | 56.0  | 2632 | 0.3137          | 0.3386 | 0.3282 |
| 0.0864        | 57.0  | 2679 | 0.3238          | 0.3386 | 0.3225 |
| 0.0632        | 58.0  | 2726 | 0.3388          | 0.3417 | 0.3338 |
| 0.0741        | 59.0  | 2773 | 0.3574          | 0.3417 | 0.3345 |
| 0.0587        | 60.0  | 2820 | 0.3617          | 0.3417 | 0.3359 |


### Framework versions

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