---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: windanam-whisper-medium
  results: []
language:
- ff
---

<!-- 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. -->

# windanam-whisper-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the [cawoylel/FulaSpeechCorpora-splited-noise_augmented](https://huggingface.co./datasets/cawoylel/FulaSpeechCorpora-splited-noise_augmented) dataset. The finetuning was done on the train and test splits of the dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1407
- Wer: 0.2006

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.5665        | 0.16  | 1000  | 0.3283          | 0.3337 |
| 0.3998        | 0.31  | 2000  | 0.2489          | 0.2825 |
| 0.35          | 0.47  | 3000  | 0.2061          | 0.2549 |
| 0.3084        | 0.62  | 4000  | 0.1842          | 0.2263 |
| 0.2603        | 0.78  | 5000  | 0.1693          | 0.2169 |
| 0.2414        | 0.93  | 6000  | 0.1592          | 0.2097 |
| 0.1604        | 1.09  | 7000  | 0.1519          | 0.2009 |
| 0.1584        | 1.24  | 8000  | 0.1474          | 0.2007 |
| 0.1442        | 1.4   | 9000  | 0.1427          | 0.1980 |
| 0.1391        | 1.55  | 10000 | 0.1407          | 0.2006 |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1