---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-05
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: tw
      split: test
      args: tw
    metrics:
    - name: Wer
      type: wer
      value: 0.75
---

<!-- 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. -->

# wav2vec2-large-xlsr-53-AsanteTwi-05

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_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7657
- Wer: 0.75

## 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: 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: 200
- num_epochs: 150

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.2241        | 16.67  | 100  | 2.1317          | 1.0    |
| 1.5168        | 33.33  | 200  | 1.1019          | 0.8125 |
| 0.7964        | 50.0   | 300  | 0.7658          | 0.75   |
| 0.4985        | 66.67  | 400  | 0.6807          | 0.625  |
| 0.3885        | 83.33  | 500  | 0.7197          | 0.5625 |
| 0.3269        | 100.0  | 600  | 0.7616          | 0.5625 |
| 0.2625        | 116.67 | 700  | 0.7000          | 0.6875 |
| 0.2595        | 133.33 | 800  | 0.7425          | 0.6875 |
| 0.2388        | 150.0  | 900  | 0.7657          | 0.75   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3