---
tags:
- generated_from_trainer
datasets:
- afrispeech-200
metrics:
- wer
model-index:
- name: afrispeech_large_A100
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: afrispeech-200
      type: afrispeech-200
      config: all
      split: train
      args: all
    metrics:
    - name: Wer
      type: wer
      value: 14.81
---

<!-- 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. -->

# afrispeech_large_A100

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the afrispeech-200 dataset.



## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

https://huggingface.co/Seyfelislem/afrispeech_large_A100/tensorboard

### Framework versions

- Transformers 4.29.1
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3