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Skier8402
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wav2vec-xls-r

Automatic Speech Recognition
Transformers
PyTorch
Swahili
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
wav2vec-xls-r
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---
language:
- sw
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: wav2vec-xls-r
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: sw
      split: test
      args: 'config: sw, split: train+test'
    metrics:
    - name: Wer
      type: wer
      value: 0.9982181245473462
---

<!-- 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. -->

# wav2vec-xls-r

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 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1585
- Wer: 0.9982

Increase the number of epochs to improve performance or use a bigger model.

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0131        | 1.53  | 1000 | 3.0846          | 1.0    |
| 2.322         | 3.07  | 2000 | 2.6234          | 1.0000 |
| 1.3523        | 4.6   | 3000 | 2.2515          | 0.9991 |
| 1.1727        | 6.13  | 4000 | 2.1585          | 0.9982 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1