---
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: 0.4469970462750246
---

<!-- 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: 0.2822
- Model Preparation Time: 0.0163
- Wer: 0.4470
- Cer: 0.0841

## 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: 8
- total_train_batch_size: 32
- 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    |
|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 53.6849       | 0.9955  | 167  | 0.2975          | 0.0163                 | 0.3955 | 0.0660 |
| 2.6944        | 1.9955  | 334  | 0.2671          | 0.0163                 | 0.3716 | 0.0612 |
| 2.4353        | 2.9955  | 501  | 0.2543          | 0.0163                 | 0.3468 | 0.0580 |
| 2.2597        | 3.9955  | 668  | 0.2459          | 0.0163                 | 0.3445 | 0.0565 |
| 2.1704        | 4.9955  | 835  | 0.2392          | 0.0163                 | 0.3251 | 0.0547 |
| 2.0144        | 5.9955  | 1002 | 0.2353          | 0.0163                 | 0.3160 | 0.0539 |
| 1.9278        | 6.9955  | 1169 | 0.2350          | 0.0163                 | 0.3143 | 0.0539 |
| 1.849         | 7.9955  | 1336 | 0.2312          | 0.0163                 | 0.3039 | 0.0520 |
| 1.811         | 8.9955  | 1503 | 0.2289          | 0.0163                 | 0.3065 | 0.0530 |
| 1.7173        | 9.9955  | 1670 | 0.2311          | 0.0163                 | 0.2967 | 0.0522 |
| 1.6504        | 10.9955 | 1837 | 0.2205          | 0.0163                 | 0.2960 | 0.0511 |
| 1.5737        | 11.9955 | 2004 | 0.2227          | 0.0163                 | 0.2904 | 0.0506 |
| 1.5547        | 12.9955 | 2171 | 0.2218          | 0.0163                 | 0.2836 | 0.0502 |
| 1.5517        | 13.9955 | 2338 | 0.2236          | 0.0163                 | 0.2917 | 0.0507 |
| 1.5031        | 14.9955 | 2505 | 0.2162          | 0.0163                 | 0.2826 | 0.0493 |
| 1.4097        | 15.9955 | 2672 | 0.2187          | 0.0163                 | 0.2773 | 0.0492 |
| 1.4143        | 16.9955 | 2839 | 0.2176          | 0.0163                 | 0.2809 | 0.0485 |
| 1.36          | 17.9955 | 3006 | 0.2200          | 0.0163                 | 0.2675 | 0.0479 |
| 1.3312        | 18.9955 | 3173 | 0.2163          | 0.0163                 | 0.2672 | 0.0482 |
| 1.3369        | 19.9955 | 3340 | 0.2199          | 0.0163                 | 0.2678 | 0.0481 |
| 1.3036        | 20.9955 | 3507 | 0.2224          | 0.0163                 | 0.2714 | 0.0482 |
| 1.2558        | 21.9955 | 3674 | 0.2244          | 0.0163                 | 0.2656 | 0.0478 |
| 1.2058        | 22.9955 | 3841 | 0.2192          | 0.0163                 | 0.2642 | 0.0481 |
| 1.167         | 23.9955 | 4008 | 0.2225          | 0.0163                 | 0.2561 | 0.0471 |
| 1.1849        | 24.9955 | 4175 | 0.2275          | 0.0163                 | 0.2610 | 0.0473 |
| 1.1378        | 25.9955 | 4342 | 0.2246          | 0.0163                 | 0.2610 | 0.0474 |
| 1.1095        | 26.9955 | 4509 | 0.2295          | 0.0163                 | 0.2538 | 0.0464 |
| 1.1042        | 27.9955 | 4676 | 0.2243          | 0.0163                 | 0.2518 | 0.0462 |
| 1.0537        | 28.9955 | 4843 | 0.2293          | 0.0163                 | 0.2531 | 0.0467 |
| 1.0335        | 29.9955 | 5010 | 0.2264          | 0.0163                 | 0.2531 | 0.0456 |
| 1.0453        | 30.9955 | 5177 | 0.2232          | 0.0163                 | 0.2525 | 0.0452 |
| 1.0099        | 31.9955 | 5344 | 0.2285          | 0.0163                 | 0.2551 | 0.0467 |
| 0.9826        | 32.9955 | 5511 | 0.2345          | 0.0163                 | 0.2570 | 0.0470 |
| 0.9615        | 33.9955 | 5678 | 0.2361          | 0.0163                 | 0.2587 | 0.0471 |
| 0.9583        | 34.9955 | 5845 | 0.2340          | 0.0163                 | 0.2528 | 0.0452 |
| 0.9421        | 35.9955 | 6012 | 0.2339          | 0.0163                 | 0.2443 | 0.0452 |
| 0.9268        | 36.9955 | 6179 | 0.2350          | 0.0163                 | 0.2518 | 0.0455 |
| 0.9003        | 37.9955 | 6346 | 0.2380          | 0.0163                 | 0.2472 | 0.0451 |
| 0.9068        | 38.9955 | 6513 | 0.2424          | 0.0163                 | 0.2515 | 0.0459 |
| 0.8845        | 39.9955 | 6680 | 0.2466          | 0.0163                 | 0.2525 | 0.0462 |
| 0.88          | 40.9955 | 6847 | 0.2423          | 0.0163                 | 0.2387 | 0.0441 |
| 0.8683        | 41.9955 | 7014 | 0.2448          | 0.0163                 | 0.2528 | 0.0463 |
| 0.8535        | 42.9955 | 7181 | 0.2498          | 0.0163                 | 0.2492 | 0.0455 |
| 0.8413        | 43.9955 | 7348 | 0.2431          | 0.0163                 | 0.2511 | 0.0463 |
| 0.8147        | 44.9955 | 7515 | 0.2416          | 0.0163                 | 0.2426 | 0.0449 |
| 0.8062        | 45.9955 | 7682 | 0.2483          | 0.0163                 | 0.2479 | 0.0455 |
| 0.7876        | 46.9955 | 7849 | 0.2477          | 0.0163                 | 0.2531 | 0.0463 |
| 0.8108        | 47.9955 | 8016 | 0.2469          | 0.0163                 | 0.2462 | 0.0454 |
| 0.7689        | 48.9955 | 8183 | 0.2539          | 0.0163                 | 0.2489 | 0.0460 |
| 0.7609        | 49.9955 | 8350 | 0.2535          | 0.0163                 | 0.2453 | 0.0446 |
| 0.7442        | 50.9955 | 8517 | 0.2603          | 0.0163                 | 0.2485 | 0.0459 |


### Framework versions

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