transformers safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_7_0 base_model:facebook/wav2vec2-large-xlsr-53 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_7_0
metrics:
- wer
model-index:
- name: luganda_wav2vec2_ctc_train_clean
  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: 0.4156354350815164
---

<!-- 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. -->

# luganda_wav2vec2_ctc_train_clean

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_7_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2835
- Wer: 0.4156

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8861        | 2.4   | 500  | 3.1284          | 1.0    |
| 2.0448        | 4.81  | 1000 | 0.5439          | 0.7131 |
| 0.6342        | 7.21  | 1500 | 0.3713          | 0.5556 |
| 0.4907        | 9.62  | 2000 | 0.3464          | 0.5015 |
| 0.4242        | 12.02 | 2500 | 0.3122          | 0.4746 |
| 0.3898        | 14.42 | 3000 | 0.3164          | 0.4634 |
| 0.357         | 16.83 | 3500 | 0.2896          | 0.4416 |
| 0.3338        | 19.23 | 4000 | 0.2880          | 0.4409 |
| 0.3223        | 21.63 | 4500 | 0.2841          | 0.4287 |
| 0.3072        | 24.04 | 5000 | 0.2849          | 0.4250 |
| 0.2974        | 26.44 | 5500 | 0.2829          | 0.4194 |
| 0.2878        | 28.85 | 6000 | 0.2835          | 0.4156 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
