---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-06
  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: 0.5
---

<!-- 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-06

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: 0.6122
- Wer: 0.5

## 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: 300

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 9.3303        | 16.67  | 100  | 5.2842          | 1.0    |
| 2.961         | 33.33  | 200  | 3.1857          | 1.0    |
| 2.8758        | 50.0   | 300  | 2.9988          | 1.0    |
| 2.8331        | 66.67  | 400  | 2.8830          | 1.0    |
| 2.4893        | 83.33  | 500  | 2.1638          | 1.0    |
| 1.1901        | 100.0  | 600  | 0.7611          | 0.5625 |
| 0.5563        | 116.67 | 700  | 0.7503          | 0.5    |
| 0.3916        | 133.33 | 800  | 0.6324          | 0.5    |
| 0.288         | 150.0  | 900  | 0.8291          | 0.5    |
| 0.2176        | 166.67 | 1000 | 0.7383          | 0.5625 |
| 0.1814        | 183.33 | 1100 | 0.6408          | 0.5    |
| 0.1749        | 200.0  | 1200 | 0.5769          | 0.5625 |
| 0.1653        | 216.67 | 1300 | 0.6512          | 0.5    |
| 0.1301        | 233.33 | 1400 | 0.6414          | 0.4375 |
| 0.1375        | 250.0  | 1500 | 0.5970          | 0.5    |
| 0.1173        | 266.67 | 1600 | 0.6119          | 0.5    |
| 0.108         | 283.33 | 1700 | 0.6325          | 0.5    |
| 0.1183        | 300.0  | 1800 | 0.6122          | 0.5    |


### Framework versions

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