---
license: apache-2.0
base_model: ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53-AsanteTwi-07
  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: 0.4375
---

<!-- 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-07

This model is a fine-tuned version of [ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second](https://huggingface.co/ayertey01/wav2vec2-large-xlsr-53-AsanteTwi-06second) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8573
- Wer: 0.4375

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0656        | 16.67 | 100  | 0.6553          | 0.5    |
| 0.0354        | 33.33 | 200  | 0.7952          | 0.5    |
| 0.0329        | 50.0  | 300  | 0.6705          | 0.4375 |
| 0.0261        | 66.67 | 400  | 0.7253          | 0.4375 |
| 0.0214        | 83.33 | 500  | 0.8056          | 0.4375 |
| 0.0236        | 100.0 | 600  | 0.8573          | 0.4375 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3