---
library_name: transformers
license: apache-2.0
base_model: razhan/whisper-base-hawrami
tags:
- generated_from_trainer
datasets:
- razhan/DOLMA-speech
metrics:
- wer
model-index:
- name: whisper-base-hawrami-transcription
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: razhan/DOLMA-speech hawrami
      type: razhan/DOLMA-speech
      args: hawrami
    metrics:
    - name: Wer
      type: wer
      value: 0.40128824476650565
---

<!-- 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-base-hawrami-transcription

This model is a fine-tuned version of [razhan/whisper-base-hawrami](https://huggingface.co/razhan/whisper-base-hawrami) on the razhan/DOLMA-speech hawrami dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2612
- Wer: 0.4013
- Cer: 0.0856

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.6798        | 1.0   | 80   | 0.5513          | 0.6855 | 0.1788 |
| 0.3095        | 2.0   | 160  | 0.2984          | 0.4486 | 0.0972 |
| 0.2673        | 3.0   | 240  | 0.2676          | 0.4143 | 0.0882 |
| 0.2428        | 4.0   | 320  | 0.2612          | 0.4013 | 0.0856 |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0