---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_14_0
metrics:
- wer
model-index:
- name: XLS-R-SWAHILI-ASR-CV14
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_14_0
      type: common_voice_14_0
      config: sw
      split: test
      args: sw
    metrics:
    - name: Wer
      type: wer
      value: 0.21479210182431807
---

<!-- 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. -->

# XLS-R-SWAHILI-ASR-CV14

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_14_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.2148
- Cer: 0.0684

## 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: 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Cer    | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:------:|
| 3.9008        | 0.33  | 400   | 0.2565 | inf             | 0.8327 |
| 0.5689        | 0.66  | 800   | 0.1306 | inf             | 0.4598 |
| 0.3838        | 1.0   | 1200  | 0.1130 | inf             | 0.3786 |
| 0.3054        | 1.33  | 1600  | 0.1032 | inf             | 0.3407 |
| 0.2877        | 1.66  | 2000  | 0.0976 | inf             | 0.3239 |
| 0.2698        | 1.99  | 2400  | 0.0952 | inf             | 0.3078 |
| 0.2285        | 2.32  | 2800  | 0.0956 | inf             | 0.3031 |
| 0.224         | 2.66  | 3200  | 0.0892 | inf             | 0.2861 |
| 0.2224        | 2.99  | 3600  | 0.0877 | inf             | 0.2809 |
| 0.1906        | 3.32  | 4000  | 0.0853 | inf             | 0.2748 |
| 0.1897        | 3.65  | 4400  | 0.0844 | inf             | 0.2707 |
| 0.183         | 3.98  | 4800  | 0.0814 | inf             | 0.2614 |
| 0.1586        | 4.32  | 5200  | 0.0809 | inf             | 0.2569 |
| 0.162         | 4.65  | 5600  | 0.0782 | inf             | 0.2493 |
| 0.1548        | 4.98  | 6000  | 0.0772 | inf             | 0.2467 |
| 0.1364        | 5.31  | 6400  | 0.0782 | inf             | 0.2459 |
| 0.1344        | 5.64  | 6800  | 0.0760 | inf             | 0.2404 |
| 0.1301        | 5.98  | 7200  | 0.0738 | inf             | 0.2346 |
| 0.1165        | 6.31  | 7600  | inf    | 0.2321          | 0.0729 |
| 0.1142        | 6.64  | 8000  | inf    | 0.2266          | 0.0719 |
| 0.1103        | 6.97  | 8400  | inf    | 0.2229          | 0.0705 |
| 0.101         | 7.3   | 8800  | inf    | 0.2203          | 0.0699 |
| 0.1006        | 7.63  | 9200  | inf    | 0.2174          | 0.0692 |
| 0.0958        | 7.97  | 9600  | inf    | 0.2160          | 0.0688 |
| 0.0896        | 8.3   | 10000 | inf    | 0.2148          | 0.0684 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1
- Datasets 2.17.0
- Tokenizers 0.15.2