---
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: 0.32969196868113837
---

<!-- 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: 0.2280
- Model Preparation Time: 0.0199
- Wer: 0.3297
- Cer: 0.0622

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 161.2211      | 0.9888  | 33   | 16.9451         | 0.0199                 | 4.5936 | 1.5848 |
| 67.6701       | 1.9888  | 66   | 3.0671          | 0.0199                 | 1.0    | 0.8589 |
| 14.5117       | 2.9888  | 99   | 0.4740          | 0.0199                 | 0.5122 | 0.0912 |
| 4.1033        | 3.9888  | 132  | 0.2786          | 0.0199                 | 0.3982 | 0.0621 |
| 3.1614        | 4.9888  | 165  | 0.2421          | 0.0199                 | 0.3497 | 0.0555 |
| 2.9473        | 5.9888  | 198  | 0.2270          | 0.0199                 | 0.3260 | 0.0517 |
| 2.7283        | 6.9888  | 231  | 0.2164          | 0.0199                 | 0.3242 | 0.05   |
| 2.5382        | 7.9888  | 264  | 0.2095          | 0.0199                 | 0.3012 | 0.0475 |
| 2.4532        | 8.9888  | 297  | 0.2051          | 0.0199                 | 0.3016 | 0.0479 |
| 2.3352        | 9.9888  | 330  | 0.1977          | 0.0199                 | 0.3037 | 0.0465 |
| 2.2913        | 10.9888 | 363  | 0.1966          | 0.0199                 | 0.2906 | 0.0460 |
| 2.2131        | 11.9888 | 396  | 0.1998          | 0.0199                 | 0.3101 | 0.0464 |
| 2.1296        | 12.9888 | 429  | 0.1912          | 0.0199                 | 0.2821 | 0.0444 |
| 2.0863        | 13.9888 | 462  | 0.1934          | 0.0199                 | 0.2796 | 0.0442 |
| 2.016         | 14.9888 | 495  | 0.1927          | 0.0199                 | 0.2761 | 0.0439 |
| 1.9625        | 15.9888 | 528  | 0.1896          | 0.0199                 | 0.2758 | 0.0438 |
| 1.9719        | 16.9888 | 561  | 0.1921          | 0.0199                 | 0.2581 | 0.0422 |
| 1.8811        | 17.9888 | 594  | 0.1910          | 0.0199                 | 0.2736 | 0.0435 |
| 1.759         | 18.9888 | 627  | 0.1913          | 0.0199                 | 0.2680 | 0.0433 |
| 1.7474        | 19.9888 | 660  | 0.1883          | 0.0199                 | 0.2602 | 0.0426 |
| 1.6931        | 20.9888 | 693  | 0.1925          | 0.0199                 | 0.2669 | 0.0430 |
| 1.6515        | 21.9888 | 726  | 0.1879          | 0.0199                 | 0.2591 | 0.0423 |
| 1.6038        | 22.9888 | 759  | 0.1919          | 0.0199                 | 0.2676 | 0.0431 |
| 1.608         | 23.9888 | 792  | 0.1960          | 0.0199                 | 0.2665 | 0.0426 |
| 1.6418        | 24.9888 | 825  | 0.1940          | 0.0199                 | 0.2612 | 0.0418 |
| 1.5068        | 25.9888 | 858  | 0.1985          | 0.0199                 | 0.2609 | 0.0427 |
| 1.5171        | 26.9888 | 891  | 0.1932          | 0.0199                 | 0.2612 | 0.0423 |


### Framework versions

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