metadata
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny AR - BH
results: []
Whisper tiny AR - BH
This model is a fine-tuned version of openai/whisper-tiny on the quran-ayat-speech-to-text dataset. It achieves the following results on the evaluation set:
- Loss: 0.0155
- Wer: 0.1082
- Cer: 0.0393
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0148 | 1.0 | 219 | 0.0134 | 0.1157 | 0.0395 |
| 0.0101 | 2.0 | 438 | 0.0105 | 0.1175 | 0.0406 |
| 0.0076 | 3.0 | 657 | 0.0099 | 0.1086 | 0.0379 |
| 0.0071 | 4.0 | 876 | 0.0100 | 0.1066 | 0.0370 |
| 0.0046 | 5.0 | 1095 | 0.0104 | 0.1081 | 0.0366 |
| 0.0026 | 6.0 | 1314 | 0.0108 | 0.1137 | 0.0421 |
| 0.003 | 7.0 | 1533 | 0.0116 | 0.1086 | 0.0391 |
| 0.0026 | 8.0 | 1752 | 0.0123 | 0.1090 | 0.0392 |
| 0.001 | 9.0 | 1971 | 0.0128 | 0.1081 | 0.0377 |
| 0.0012 | 10.0 | 2190 | 0.0133 | 0.1097 | 0.0391 |
| 0.001 | 11.0 | 2409 | 0.0137 | 0.1091 | 0.0373 |
| 0.0004 | 12.0 | 2628 | 0.0141 | 0.1081 | 0.0379 |
| 0.0009 | 13.0 | 2847 | 0.0143 | 0.1064 | 0.0363 |
| 0.0005 | 14.0 | 3066 | 0.0157 | 0.1086 | 0.0397 |
| 0.0009 | 15.0 | 3285 | 0.0145 | 0.1071 | 0.0370 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1