---
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
datasets:
  - arbml/mgb2
metrics:
  - wer
model-index:
  - name: Whisper Large V2 - Zaid Alyafeai
    results:
      - task:
          name: Automatic Speech Recognition
          type: 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:
          - name: Wer
            type: wer
            value: 38.23
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ar_eg
          split: test
          args: ar
        metrics:
          - name: Wer
            type: wer
            value: 11.60
---


<!-- 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-large-v2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8091
- Wer: 17.7875

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.2528        | 0.2   | 2000  | 0.9370          | 22.1311 |
| 0.2718        | 0.4   | 4000  | 0.8721          | 24.9294 |
| 0.2745        | 0.6   | 6000  | 0.8770          | 20.5292 |
| 0.2157        | 0.8   | 8000  | 0.8774          | 18.1018 |
| 0.1729        | 1.0   | 10000 | 0.8091          | 17.7875 |


### Framework versions

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