---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
  name: hausa-4-ha-wa2vec-data-aug-xls-r-300m
---

<!-- 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. -->

# hausa-4-ha-wa2vec-data-aug-xls-r-300m

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: 0.3071
- Wer: 0.3304

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 14.9837       | 0.46  | 30   | 10.7164         | 1.0    |
| 7.0027        | 0.92  | 60   | 3.9322          | 1.0    |
| 3.668         | 1.38  | 90   | 3.0115          | 1.0    |
| 2.9374        | 1.84  | 120  | 2.8464          | 1.0    |
| 2.8864        | 2.31  | 150  | 2.8234          | 1.0    |
| 2.8143        | 2.76  | 180  | 2.8158          | 1.0    |
| 2.8412        | 3.23  | 210  | 2.7971          | 1.0    |
| 2.7953        | 3.69  | 240  | 2.7910          | 1.0    |
| 2.835         | 4.15  | 270  | 2.7845          | 1.0    |
| 2.7802        | 4.61  | 300  | 2.7814          | 1.0    |
| 2.8292        | 5.08  | 330  | 2.7621          | 1.0    |
| 2.7618        | 5.53  | 360  | 2.7534          | 1.0    |
| 2.753         | 5.99  | 390  | 2.7468          | 1.0    |
| 2.7898        | 6.46  | 420  | 2.7431          | 1.0    |
| 2.7279        | 6.92  | 450  | 2.7243          | 1.0    |
| 2.7701        | 7.38  | 480  | 2.6845          | 1.0    |
| 2.6309        | 7.84  | 510  | 2.4668          | 1.0    |
| 2.3744        | 8.31  | 540  | 1.9042          | 1.0    |
| 1.6864        | 8.76  | 570  | 1.1582          | 0.9979 |
| 1.2278        | 9.23  | 600  | 0.8350          | 0.7765 |
| 0.987         | 9.69  | 630  | 0.7210          | 0.7456 |
| 0.8785        | 10.15 | 660  | 0.5951          | 0.6531 |
| 0.7311        | 10.61 | 690  | 0.5486          | 0.6141 |
| 0.7005        | 11.08 | 720  | 0.4986          | 0.5617 |
| 0.6442        | 11.53 | 750  | 0.4720          | 0.5658 |
| 0.5662        | 11.99 | 780  | 0.4476          | 0.5195 |
| 0.5385        | 12.46 | 810  | 0.4283          | 0.4938 |
| 0.5376        | 12.92 | 840  | 0.4029          | 0.4723 |
| 0.48          | 13.38 | 870  | 0.4047          | 0.4599 |
| 0.4786        | 13.84 | 900  | 0.3855          | 0.4378 |
| 0.4734        | 14.31 | 930  | 0.3843          | 0.4594 |
| 0.4572        | 14.76 | 960  | 0.3777          | 0.4188 |
| 0.406         | 15.23 | 990  | 0.3564          | 0.4060 |
| 0.4264        | 15.69 | 1020 | 0.3419          | 0.3983 |
| 0.3785        | 16.15 | 1050 | 0.3583          | 0.4013 |
| 0.3686        | 16.61 | 1080 | 0.3445          | 0.3844 |
| 0.3797        | 17.08 | 1110 | 0.3318          | 0.3839 |
| 0.3492        | 17.53 | 1140 | 0.3350          | 0.3808 |
| 0.3472        | 17.99 | 1170 | 0.3305          | 0.3772 |
| 0.3442        | 18.46 | 1200 | 0.3280          | 0.3684 |
| 0.3283        | 18.92 | 1230 | 0.3414          | 0.3762 |
| 0.3378        | 19.38 | 1260 | 0.3224          | 0.3607 |
| 0.3296        | 19.84 | 1290 | 0.3127          | 0.3669 |
| 0.3206        | 20.31 | 1320 | 0.3183          | 0.3546 |
| 0.3157        | 20.76 | 1350 | 0.3223          | 0.3402 |
| 0.3165        | 21.23 | 1380 | 0.3203          | 0.3371 |
| 0.3062        | 21.69 | 1410 | 0.3198          | 0.3499 |
| 0.2961        | 22.15 | 1440 | 0.3221          | 0.3438 |
| 0.2895        | 22.61 | 1470 | 0.3238          | 0.3469 |
| 0.2919        | 23.08 | 1500 | 0.3123          | 0.3397 |
| 0.2719        | 23.53 | 1530 | 0.3172          | 0.3412 |
| 0.2646        | 23.99 | 1560 | 0.3128          | 0.3345 |
| 0.2857        | 24.46 | 1590 | 0.3113          | 0.3366 |
| 0.2704        | 24.92 | 1620 | 0.3126          | 0.3433 |
| 0.2868        | 25.38 | 1650 | 0.3126          | 0.3402 |
| 0.2571        | 25.84 | 1680 | 0.3080          | 0.3397 |
| 0.2682        | 26.31 | 1710 | 0.3076          | 0.3371 |
| 0.2881        | 26.76 | 1740 | 0.3051          | 0.3330 |
| 0.2847        | 27.23 | 1770 | 0.3025          | 0.3381 |
| 0.2586        | 27.69 | 1800 | 0.3032          | 0.3350 |
| 0.2494        | 28.15 | 1830 | 0.3092          | 0.3345 |
| 0.2521        | 28.61 | 1860 | 0.3087          | 0.3340 |
| 0.2605        | 29.08 | 1890 | 0.3077          | 0.3320 |
| 0.2479        | 29.53 | 1920 | 0.3070          | 0.3304 |
| 0.2398        | 29.99 | 1950 | 0.3071          | 0.3304 |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3