transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:nadsoft/QASR-Speech-Resource base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- whisper-event
- generated_from_trainer
datasets:
- nadsoft/QASR-Speech-Resource
metrics:
- wer
model-index:
- name: Whisper Small Arabic
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nadsoft/QASR-Speech-Resource default
      type: nadsoft/QASR-Speech-Resource
    metrics:
    - name: Wer
      type: wer
      value: 42.76086285863452
---

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# Whisper Small Arabic

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the nadsoft/QASR-Speech-Resource default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5583
- Wer: 42.7609

## 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: 32
- 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7005        | 0.2   | 2000  | 0.7135          | 51.5366 |
| 0.6267        | 0.4   | 4000  | 0.6309          | 50.9433 |
| 0.5886        | 0.6   | 6000  | 0.5892          | 50.0225 |
| 0.5627        | 0.8   | 8000  | 0.5679          | 43.9450 |
| 0.5694        | 1.0   | 10000 | 0.5583          | 42.7609 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1.dev0
- Tokenizers 0.15.1
