transformers tensorboard safetensors whisper automatic-speech-recognition whisper-event generated_from_trainer dataset:google/fleurs base_model:arun100/whisper-small-ar-1 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: arun100/whisper-small-ar-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small Arabic
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: google/fleurs ar_eg
      type: google/fleurs
      config: ar_eg
      split: test
      args: ar_eg
    metrics:
    - name: Wer
      type: wer
      value: 28.809032414714096
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Arabic

This model is a fine-tuned version of [arun100/whisper-small-ar-1](https://huggingface.co/arun100/whisper-small-ar-1) on the google/fleurs ar_eg dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4548
- Wer: 28.8090

## 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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2414        | 52.0  | 500  | 0.3988          | 30.5694 |
| 0.0412        | 105.0 | 1000 | 0.4284          | 30.5694 |
| 0.0147        | 157.0 | 1500 | 0.4548          | 28.8090 |
| 0.0084        | 210.0 | 2000 | 0.4738          | 29.1125 |
| 0.0057        | 263.0 | 2500 | 0.4888          | 29.3553 |
| 0.0043        | 315.0 | 3000 | 0.5010          | 29.2218 |
| 0.0034        | 368.0 | 3500 | 0.5108          | 29.4889 |
| 0.0029        | 421.0 | 4000 | 0.5185          | 29.5010 |
| 0.0026        | 473.0 | 4500 | 0.5236          | 29.4889 |
| 0.0024        | 526.0 | 5000 | 0.5256          | 29.5375 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0
