---
library_name: transformers
license: apache-2.0
base_model: Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper-smal-ar-testing-kale
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: None
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 307.8198198198198
---

<!-- 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-smal-ar-testing-kale

This model is a fine-tuned version of [Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small](https://huggingface.co/Salama1429/KalemaTech-Arabic-STT-ASR-based-on-Whisper-Small) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6230
- Wer: 307.8198

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 1
- training_steps: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.6566        | 0.0032 | 2    | 2.6230          | 307.8198 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1