---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- afrispeech-200
metrics:
- wer
model-index:
- name: whisper-small-hi-2400_500_100
  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: 0.6376484560570072
---

<!-- 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. -->

# whisper-small-hi-2400_500_100

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the afrispeech-200 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1136
- Wer: 0.6376

## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 900
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.0658        | 0.17  | 150  | 2.3108          | 1.0536 |
| 1.4738        | 0.33  | 300  | 1.3138          | 1.0395 |
| 0.8823        | 1.17  | 450  | 1.2148          | 0.7992 |
| 1.1971        | 1.33  | 600  | 1.1466          | 0.7340 |
| 0.7529        | 2.17  | 750  | 1.1256          | 0.6723 |
| 1.1194        | 2.33  | 900  | 1.1136          | 0.6376 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2