---
library_name: transformers
language:
- xh
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- NCHLT_speech_corpus
metrics:
- wer
model-index:
- name: facebook mms-1b-all xhosa - Beijuka Bruno
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: NCHLT_speech_corpus/Xhosa
      type: NCHLT_speech_corpus
    metrics:
    - name: Wer
      type: wer
      value: 0.7415725069154672
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# facebook mms-1b-all xhosa - Beijuka Bruno

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NCHLT_speech_corpus/Xhosa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5077
- Model Preparation Time: 0.0185
- Wer: 0.7416
- Cer: 0.1466

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-----:|:------:|:---------------:|:----------------------:|:------:|:------:|
| 3.0339        | 1.0   | 2604   | 0.2173          | 0.0185                 | 0.3580 | 0.0532 |
| 1.074         | 2.0   | 5208   | 0.2030          | 0.0185                 | 0.3267 | 0.0492 |
| 1.007         | 3.0   | 7812   | 0.2000          | 0.0185                 | 0.3209 | 0.0485 |
| 0.9601        | 4.0   | 10416  | 0.1937          | 0.0185                 | 0.3047 | 0.0468 |
| 0.9269        | 5.0   | 13020  | 0.1908          | 0.0185                 | 0.3071 | 0.0460 |
| 0.8968        | 6.0   | 15624  | 0.1912          | 0.0185                 | 0.3012 | 0.0455 |
| 0.8704        | 7.0   | 18228  | 0.1900          | 0.0185                 | 0.2990 | 0.0450 |
| 0.854         | 8.0   | 20832  | 0.1900          | 0.0185                 | 0.2993 | 0.0452 |
| 0.8287        | 9.0   | 23436  | 0.1888          | 0.0185                 | 0.3047 | 0.0454 |
| 0.8122        | 10.0  | 26040  | 0.1881          | 0.0185                 | 0.2976 | 0.0445 |
| 0.7944        | 11.0  | 28644  | 0.1850          | 0.0185                 | 0.2916 | 0.0437 |
| 0.776         | 12.0  | 31248  | 0.1807          | 0.0185                 | 0.2820 | 0.0426 |
| 0.7557        | 13.0  | 33852  | 0.1862          | 0.0185                 | 0.2858 | 0.0429 |
| 0.7484        | 14.0  | 36456  | 0.1818          | 0.0185                 | 0.2845 | 0.0428 |
| 0.7347        | 15.0  | 39060  | 0.1842          | 0.0185                 | 0.2845 | 0.0434 |
| 0.7262        | 16.0  | 41664  | 0.1830          | 0.0185                 | 0.2873 | 0.0434 |
| 0.713         | 17.0  | 44268  | 0.1829          | 0.0185                 | 0.2850 | 0.0431 |
| 0.6957        | 18.0  | 46872  | 0.1829          | 0.0185                 | 0.2803 | 0.0420 |
| 0.6867        | 19.0  | 49476  | 0.1813          | 0.0185                 | 0.2750 | 0.0414 |
| 0.6716        | 20.0  | 52080  | 0.1812          | 0.0185                 | 0.2743 | 0.0416 |
| 0.668         | 21.0  | 54684  | 0.1838          | 0.0185                 | 0.2773 | 0.0423 |
| 0.662         | 22.0  | 57288  | 0.1875          | 0.0185                 | 0.2743 | 0.0418 |
| 0.6471        | 23.0  | 59892  | 0.1828          | 0.0185                 | 0.2779 | 0.0422 |
| 0.6414        | 24.0  | 62496  | 0.1863          | 0.0185                 | 0.2770 | 0.0416 |
| 0.6322        | 25.0  | 65100  | 0.1851          | 0.0185                 | 0.2754 | 0.0412 |
| 0.6238        | 26.0  | 67704  | 0.1847          | 0.0185                 | 0.2811 | 0.0422 |
| 0.6151        | 27.0  | 70308  | 0.1830          | 0.0185                 | 0.2682 | 0.0408 |
| 0.6046        | 28.0  | 72912  | 0.1811          | 0.0185                 | 0.2700 | 0.0408 |
| 0.5973        | 29.0  | 75516  | 0.1841          | 0.0185                 | 0.2694 | 0.0412 |
| 0.5897        | 30.0  | 78120  | 0.1826          | 0.0185                 | 0.2653 | 0.0404 |
| 0.5855        | 31.0  | 80724  | 0.1826          | 0.0185                 | 0.2653 | 0.0407 |
| 0.5738        | 32.0  | 83328  | 0.1801          | 0.0185                 | 0.2712 | 0.0411 |
| 0.5664        | 33.0  | 85932  | 0.1837          | 0.0185                 | 0.2682 | 0.0408 |
| 0.5607        | 34.0  | 88536  | 0.1870          | 0.0185                 | 0.2646 | 0.0405 |
| 0.5556        | 35.0  | 91140  | 0.1848          | 0.0185                 | 0.2665 | 0.0407 |
| 0.5493        | 36.0  | 93744  | 0.1822          | 0.0185                 | 0.2597 | 0.0395 |
| 0.5426        | 37.0  | 96348  | 0.1833          | 0.0185                 | 0.2693 | 0.0405 |
| 0.536         | 38.0  | 98952  | 0.1843          | 0.0185                 | 0.2672 | 0.0404 |
| 0.5231        | 39.0  | 101556 | 0.1833          | 0.0185                 | 0.2696 | 0.0405 |
| 0.5204        | 40.0  | 104160 | 0.1833          | 0.0185                 | 0.2663 | 0.0401 |
| 0.5167        | 41.0  | 106764 | 0.1818          | 0.0185                 | 0.2637 | 0.0395 |
| 0.513         | 42.0  | 109368 | 0.1842          | 0.0185                 | 0.2643 | 0.0396 |
| 0.506         | 43.0  | 111972 | 0.1876          | 0.0185                 | 0.2661 | 0.0401 |
| 0.4976        | 44.0  | 114576 | 0.1890          | 0.0185                 | 0.2615 | 0.0400 |
| 0.4904        | 45.0  | 117180 | 0.1842          | 0.0185                 | 0.2587 | 0.0392 |
| 0.4864        | 46.0  | 119784 | 0.1886          | 0.0185                 | 0.2600 | 0.0391 |
| 0.4814        | 47.0  | 122388 | 0.1849          | 0.0185                 | 0.2627 | 0.0398 |
| 0.4821        | 48.0  | 124992 | 0.1860          | 0.0185                 | 0.2583 | 0.0390 |
| 0.4662        | 49.0  | 127596 | 0.1906          | 0.0185                 | 0.2624 | 0.0397 |
| 0.4632        | 50.0  | 130200 | 0.1881          | 0.0185                 | 0.2603 | 0.0393 |
| 0.465         | 51.0  | 132804 | 0.1876          | 0.0185                 | 0.2627 | 0.0396 |
| 0.4549        | 52.0  | 135408 | 0.1898          | 0.0185                 | 0.2596 | 0.0393 |
| 0.4532        | 53.0  | 138012 | 0.1916          | 0.0185                 | 0.2606 | 0.0395 |
| 0.4478        | 54.0  | 140616 | 0.1912          | 0.0185                 | 0.2617 | 0.0398 |
| 0.4418        | 55.0  | 143220 | 0.1935          | 0.0185                 | 0.2600 | 0.0393 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0