---
language:
- ar
license: apache-2.0
tags:
- ar-asr-leaderboard
- generated_from_trainer
datasets:
- AXAI/client
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper small Ar - AxAI
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Client
      type: AXAI/client
      config: default
      split: None
      args: default
    metrics:
    - type: wer
      value: 84.11458333333334
      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 small Ar - AxAI

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Client dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5990
- Wer: 84.1146

## 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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.8044        | 6.37   | 200  | 1.2417          | 69.9219 |
| 0.036         | 12.75  | 400  | 1.1791          | 60.9375 |
| 0.0108        | 19.12  | 600  | 1.3128          | 80.2083 |
| 0.0035        | 25.5   | 800  | 1.3641          | 62.6953 |
| 0.0009        | 31.87  | 1000 | 1.4066          | 66.6016 |
| 0.0004        | 38.25  | 1200 | 1.4410          | 64.5833 |
| 0.0003        | 44.62  | 1400 | 1.4712          | 63.3464 |
| 0.0002        | 51.0   | 1600 | 1.4927          | 63.6068 |
| 0.0002        | 57.37  | 1800 | 1.5102          | 67.1875 |
| 0.0002        | 63.75  | 2000 | 1.5254          | 66.6016 |
| 0.0001        | 70.12  | 2200 | 1.5393          | 77.8646 |
| 0.0001        | 76.49  | 2400 | 1.5512          | 77.9297 |
| 0.0001        | 82.87  | 2600 | 1.5616          | 77.7344 |
| 0.0001        | 89.24  | 2800 | 1.5710          | 83.1380 |
| 0.0001        | 95.62  | 3000 | 1.5791          | 88.0859 |
| 0.0001        | 101.99 | 3200 | 1.5854          | 88.1510 |
| 0.0001        | 108.37 | 3400 | 1.5910          | 88.0859 |
| 0.0001        | 114.74 | 3600 | 1.5953          | 84.1146 |
| 0.0001        | 121.12 | 3800 | 1.5978          | 84.1797 |
| 0.0001        | 127.49 | 4000 | 1.5990          | 84.1146 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2