transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer ar dataset:nadsoft/arabic-98 base_model:nadsoft/hamsa-v0.1-beta license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ar
license: apache-2.0
base_model: nadsoft/hamsa-v0.1-beta
tags:
- generated_from_trainer
datasets:
- nadsoft/arabic-98
metrics:
- wer
model-index:
- name: hamsa-beta-v0.3Q
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nadsoft/arabic-98
      type: nadsoft/arabic-98
    metrics:
    - name: Wer
      type: wer
      value: 19.302853050017905
---

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# hamsa-beta-v0.3Q

This model is a fine-tuned version of [nadsoft/hamsa-v0.1-beta](https://huggingface.co/nadsoft/hamsa-v0.1-beta) on the nadsoft/arabic-98 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2362
- Wer Ortho: 21.12
- Wer: 19.3029

## 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
- 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 Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.2617        | 0.25  | 1000 | 0.2684          | 22.16     | 18.8134 |
| 0.227         | 0.5   | 2000 | 0.2565          | 18.6971   | 16.7482 |
| 0.2585        | 0.75  | 3000 | 0.2442          | 18.2400   | 16.3304 |
| 0.2632        | 1.0   | 4000 | 0.2362          | 21.12     | 19.3029 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
