metadata

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

whisper-base-hawrami-transcription

This model is a fine-tuned version of 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