---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: whisper-medium-ar-original
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - type: wer
      value: 14.108618654073199
      name: Wer
---

<!-- 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-medium-ar-original

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1852
- Wer: 14.1086

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.115         | 1.01  | 400  | 0.1204          | 18.6541 |
| 0.0774        | 2.02  | 800  | 0.1074          | 15.5844 |
| 0.0438        | 3.03  | 1200 | 0.1160          | 16.4699 |
| 0.0233        | 4.04  | 1600 | 0.1279          | 15.1122 |
| 0.0131        | 5.05  | 2000 | 0.1350          | 15.5254 |
| 0.0051        | 6.06  | 2400 | 0.1455          | 14.9941 |
| 0.0035        | 7.07  | 2800 | 0.1464          | 14.1677 |
| 0.0032        | 8.08  | 3200 | 0.1545          | 14.8170 |
| 0.0013        | 9.09  | 3600 | 0.1623          | 13.8725 |
| 0.0013        | 10.1  | 4000 | 0.1543          | 13.4002 |
| 0.0006        | 11.11 | 4400 | 0.1653          | 14.1677 |
| 0.0006        | 12.12 | 4800 | 0.1699          | 13.7544 |
| 0.0003        | 13.13 | 5200 | 0.1705          | 13.4593 |
| 0.0001        | 14.14 | 5600 | 0.1733          | 13.6954 |
| 0.0002        | 15.15 | 6000 | 0.1768          | 13.8725 |
| 0.0001        | 16.16 | 6400 | 0.1786          | 13.7544 |
| 0.0           | 17.17 | 6800 | 0.1826          | 13.9906 |
| 0.0           | 18.18 | 7200 | 0.1839          | 14.0496 |
| 0.0           | 19.19 | 7600 | 0.1848          | 14.0496 |
| 0.0           | 20.2  | 8000 | 0.1852          | 14.1086 |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.8.0
- Tokenizers 0.13.2