transformers tensorboard 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
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
base_model: facebook/wav2vec2-base
model-index:
- name: luganda_wav2vec2_ctc_tokenizer
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_7_0
      type: common_voice_7_0
      config: lg
      split: None
      args: lg
    metrics:
    - type: wer
      value: 0.5608917697898251
      name: Wer
---

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# luganda_wav2vec2_ctc_tokenizer

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: 0.5588
- Wer: 0.5609

## 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: 32
- 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: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.1365        | 2.4   | 500  | 1.9598          | 1.0    |
| 0.5695        | 4.81  | 1000 | 0.5853          | 0.7329 |
| 0.176         | 7.21  | 1500 | 0.5381          | 0.6747 |
| 0.0845        | 9.62  | 2000 | 0.5128          | 0.6270 |
| 0.0424        | 12.02 | 2500 | 0.4651          | 0.6014 |
| 0.0127        | 14.42 | 3000 | 0.5395          | 0.6049 |
| -0.0063       | 16.83 | 3500 | 0.5169          | 0.5842 |
| -0.0212       | 19.23 | 4000 | 0.4990          | 0.5833 |
| -0.0336       | 21.63 | 4500 | 0.5318          | 0.5680 |
| -0.0424       | 24.04 | 5000 | 0.5465          | 0.5702 |
| -0.0495       | 26.44 | 5500 | 0.5541          | 0.5637 |
| -0.0565       | 28.85 | 6000 | 0.5588          | 0.5609 |


### Framework versions

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