---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- arbml/mgb2
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium ar - Zaid Alyafeai
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0
      type: mozilla-foundation/common_voice_11_0
      config: ar
      split: test
      args: ar
    metrics:
    - type: wer
      value: 34.28
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ar_eg
      split: test
      args: ar
    metrics:
    - type: wer
      value: 12.04
      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. -->

# openai/whisper-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8488
- Wer: 16.5882

## 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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2963        | 0.1   | 1000  | 0.9115          | 27.3641 |
| 0.2676        | 0.2   | 2000  | 0.8796          | 24.1024 |
| 0.3166        | 0.3   | 3000  | 0.8467          | 20.1700 |
| 0.2797        | 0.4   | 4000  | 0.8756          | 29.4889 |
| 0.2302        | 0.5   | 5000  | 0.8523          | 19.6414 |
| 0.2803        | 0.6   | 6000  | 0.8715          | 19.7413 |
| 0.2794        | 0.7   | 7000  | 0.8548          | 18.6840 |
| 0.2173        | 0.8   | 8000  | 0.8543          | 17.9019 |
| 0.217         | 0.9   | 9000  | 0.8518          | 16.3840 |
| 0.1718        | 1.0   | 10000 | 0.8488          | 16.5882 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2