metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- automatic-speech-recognition
- arabic
- generated_from_trainer
datasets:
- itskavya/gp
metrics:
- wer
model-index:
- name: Whisper Tiny Informal Arabic
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Informal Arabic
type: itskavya/gp
config: default
split: None
args: default
metrics:
- name: Wer
type: wer
value: 63.70745170193193
Whisper Tiny Informal Arabic
This model is a fine-tuned version of openai/whisper-tiny on the Informal Arabic dataset. It achieves the following results on the evaluation set:
- Loss: 1.1448
- Wer: 63.7075
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5883 | 4.0650 | 1000 | 0.8899 | 66.7433 |
| 0.2235 | 8.1301 | 2000 | 0.9200 | 63.0635 |
| 0.0966 | 12.1951 | 3000 | 1.0207 | 63.3211 |
| 0.0389 | 16.2602 | 4000 | 1.1064 | 63.1555 |
| 0.0275 | 20.3252 | 5000 | 1.1448 | 63.7075 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0