transformers safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_7_0 base_model:facebook/wav2vec2-base license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
model-index:
- name: luganda_wav2vec2_ctc
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_7_0
      type: common_voice_7_0
      config: lg
      split: None
      args: lg
    metrics:
    - name: Wer
      type: wer
      value: 0.5421986512145617
---

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# luganda_wav2vec2_ctc

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7622
- Wer: 0.5422

## 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: 48
- 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: 1000
- num_epochs: 60
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2675        | 3.6   | 500  | 1.9999          | 0.9999 |
| 0.5754        | 7.19  | 1000 | 0.6976          | 0.7050 |
| 0.231         | 10.79 | 1500 | 0.6153          | 0.6440 |
| 0.1557        | 14.39 | 2000 | 0.6581          | 0.6130 |
| 0.1221        | 17.99 | 2500 | 0.6718          | 0.6063 |
| 0.1013        | 21.58 | 3000 | 0.6711          | 0.5934 |
| 0.0871        | 25.18 | 3500 | 0.6728          | 0.5731 |
| 0.0751        | 28.78 | 4000 | 0.6729          | 0.5726 |
| 0.0666        | 32.37 | 4500 | 0.6884          | 0.5689 |
| 0.0604        | 35.97 | 5000 | 0.7452          | 0.5609 |
| 0.0543        | 39.57 | 5500 | 0.7302          | 0.5616 |
| 0.0488        | 43.17 | 6000 | 0.7414          | 0.5480 |
| 0.0448        | 46.76 | 6500 | 0.7662          | 0.5560 |
| 0.042         | 50.36 | 7000 | 0.7629          | 0.5433 |
| 0.038         | 53.96 | 7500 | 0.7582          | 0.5479 |
| 0.0353        | 57.55 | 8000 | 0.7622          | 0.5422 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
