---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-Fleurs_AMMI_AFRIVOICE_LRSC-ln-10hrs-v2
  results: []
---

<!-- 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. -->

# wav2vec2-xls-r-300m-Fleurs_AMMI_AFRIVOICE_LRSC-ln-10hrs-v2

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4351
- Wer: 0.2577
- Cer: 0.0833

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- 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
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 7.7647        | 1.0   | 768   | 3.1933          | 1.0    | 1.0    |
| 3.0093        | 2.0   | 1536  | 2.8646          | 1.0    | 1.0    |
| 2.8666        | 3.0   | 2304  | 2.8188          | 1.0    | 1.0    |
| 2.7248        | 4.0   | 3072  | 2.2736          | 1.0    | 0.7102 |
| 1.8518        | 5.0   | 3840  | 1.1205          | 0.9523 | 0.2684 |
| 1.2788        | 6.0   | 4608  | 0.8644          | 0.6379 | 0.1739 |
| 1.0685        | 7.0   | 5376  | 0.7393          | 0.5324 | 0.1498 |
| 0.9306        | 8.0   | 6144  | 0.6640          | 0.4750 | 0.1369 |
| 0.8376        | 9.0   | 6912  | 0.6044          | 0.4290 | 0.1282 |
| 0.7758        | 10.0  | 7680  | 0.5699          | 0.4055 | 0.1215 |
| 0.7303        | 11.0  | 8448  | 0.5588          | 0.3849 | 0.1159 |
| 0.6748        | 12.0  | 9216  | 0.5249          | 0.3716 | 0.1115 |
| 0.6509        | 13.0  | 9984  | 0.5161          | 0.3550 | 0.1074 |
| 0.6141        | 14.0  | 10752 | 0.5091          | 0.3599 | 0.1076 |
| 0.5903        | 15.0  | 11520 | 0.4849          | 0.3486 | 0.1050 |
| 0.5676        | 16.0  | 12288 | 0.4614          | 0.3460 | 0.1053 |
| 0.5421        | 17.0  | 13056 | 0.4494          | 0.3476 | 0.1080 |
| 0.5363        | 18.0  | 13824 | 0.4598          | 0.3189 | 0.0980 |
| 0.5139        | 19.0  | 14592 | 0.4553          | 0.3157 | 0.0976 |
| 0.5002        | 20.0  | 15360 | 0.4492          | 0.3118 | 0.0960 |
| 0.4847        | 21.0  | 16128 | 0.4415          | 0.3145 | 0.0972 |
| 0.467         | 22.0  | 16896 | 0.4287          | 0.2988 | 0.0923 |
| 0.4558        | 23.0  | 17664 | 0.4367          | 0.2970 | 0.0927 |
| 0.4442        | 24.0  | 18432 | 0.4265          | 0.3019 | 0.0951 |
| 0.4274        | 25.0  | 19200 | 0.4247          | 0.2910 | 0.0912 |
| 0.424         | 26.0  | 19968 | 0.4205          | 0.2900 | 0.0915 |
| 0.403         | 27.0  | 20736 | 0.4131          | 0.2909 | 0.0915 |
| 0.4017        | 28.0  | 21504 | 0.4068          | 0.3002 | 0.0985 |
| 0.393         | 29.0  | 22272 | 0.4118          | 0.2895 | 0.0910 |
| 0.3852        | 30.0  | 23040 | 0.4275          | 0.2857 | 0.0897 |
| 0.3783        | 31.0  | 23808 | 0.4145          | 0.2852 | 0.0911 |
| 0.3776        | 32.0  | 24576 | 0.4200          | 0.2781 | 0.0882 |
| 0.3667        | 33.0  | 25344 | 0.4174          | 0.2778 | 0.0876 |
| 0.3582        | 34.0  | 26112 | 0.4129          | 0.2827 | 0.0902 |
| 0.3517        | 35.0  | 26880 | 0.4231          | 0.2780 | 0.0870 |
| 0.3479        | 36.0  | 27648 | 0.4058          | 0.2806 | 0.0910 |
| 0.3394        | 37.0  | 28416 | 0.4375          | 0.2757 | 0.0868 |
| 0.3336        | 38.0  | 29184 | 0.4320          | 0.2723 | 0.0861 |
| 0.3267        | 39.0  | 29952 | 0.4165          | 0.2750 | 0.0871 |
| 0.3179        | 40.0  | 30720 | 0.4198          | 0.2729 | 0.0865 |
| 0.3157        | 41.0  | 31488 | 0.4152          | 0.2721 | 0.0861 |
| 0.3097        | 42.0  | 32256 | 0.4007          | 0.2753 | 0.0886 |
| 0.306         | 43.0  | 33024 | 0.4471          | 0.2705 | 0.0853 |
| 0.3061        | 44.0  | 33792 | 0.4154          | 0.2649 | 0.0849 |
| 0.2931        | 45.0  | 34560 | 0.4506          | 0.2611 | 0.0832 |
| 0.2994        | 46.0  | 35328 | 0.4287          | 0.2669 | 0.0851 |
| 0.2972        | 47.0  | 36096 | 0.4188          | 0.2670 | 0.0859 |
| 0.2836        | 48.0  | 36864 | 0.4350          | 0.2554 | 0.0828 |
| 0.283         | 49.0  | 37632 | 0.4167          | 0.2620 | 0.0845 |
| 0.2765        | 50.0  | 38400 | 0.4314          | 0.2634 | 0.0849 |
| 0.278         | 51.0  | 39168 | 0.4097          | 0.2702 | 0.0892 |
| 0.2744        | 52.0  | 39936 | 0.4255          | 0.2591 | 0.0835 |
| 0.2662        | 53.0  | 40704 | 0.4293          | 0.2595 | 0.0836 |
| 0.2663        | 54.0  | 41472 | 0.4423          | 0.2583 | 0.0826 |
| 0.264         | 55.0  | 42240 | 0.4313          | 0.2587 | 0.0835 |
| 0.2549        | 56.0  | 43008 | 0.4441          | 0.2614 | 0.0842 |
| 0.2586        | 57.0  | 43776 | 0.4259          | 0.2611 | 0.0857 |
| 0.2577        | 58.0  | 44544 | 0.4258          | 0.2570 | 0.0837 |
| 0.2486        | 59.0  | 45312 | 0.4332          | 0.2606 | 0.0845 |
| 0.2473        | 60.0  | 46080 | 0.4402          | 0.2589 | 0.0834 |
| 0.2464        | 61.0  | 46848 | 0.4263          | 0.2567 | 0.0826 |
| 0.2442        | 62.0  | 47616 | 0.4527          | 0.2563 | 0.0819 |
| 0.2444        | 63.0  | 48384 | 0.4351          | 0.2577 | 0.0833 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1