---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-04
  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: 0.625
---

<!-- 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-04

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: 0.7250
- Wer: 0.625

## 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: 0.0003
- 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: 100
- num_epochs: 90

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 13.2642       | 8.33  | 50   | 4.7327          | 1.0   |
| 3.1075        | 16.67 | 100  | 3.1680          | 1.0   |
| 2.8849        | 25.0  | 150  | 2.9745          | 1.0   |
| 2.8553        | 33.33 | 200  | 2.9167          | 1.0   |
| 2.8333        | 41.67 | 250  | 2.8538          | 1.0   |
| 2.6501        | 50.0  | 300  | 2.3417          | 1.0   |
| 1.8966        | 58.33 | 350  | 1.1529          | 0.875 |
| 0.9431        | 66.67 | 400  | 0.8519          | 0.75  |
| 0.5951        | 75.0  | 450  | 0.7970          | 0.625 |
| 0.444         | 83.33 | 500  | 0.7250          | 0.625 |


### Framework versions

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