|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- ar |
|
|
license: apache-2.0 |
|
|
base_model: openai/whisper-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: Whisper base AR - BA |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- 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 AR - BA |
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the quran-ayat-speech-to-text dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1029 |
|
|
- Wer: 0.2133 |
|
|
|
|
|
## 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: 0.0001 |
|
|
- train_batch_size: 8 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 32 |
|
|
- 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 |
|
|
- num_epochs: 15 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-------:|:----:|:---------------:|:------:| |
|
|
| 2.6022 | 1.0 | 154 | 0.0981 | 0.2051 | |
|
|
| 2.386 | 2.0 | 308 | 0.0994 | 0.2067 | |
|
|
| 1.9412 | 3.0 | 462 | 0.0996 | 0.2022 | |
|
|
| 1.824 | 4.0 | 616 | 0.0998 | 0.2045 | |
|
|
| 1.6295 | 5.0 | 770 | 0.0976 | 0.2101 | |
|
|
| 1.458 | 6.0 | 924 | 0.0982 | 0.2007 | |
|
|
| 1.2992 | 7.0 | 1078 | 0.0959 | 0.2063 | |
|
|
| 1.1839 | 8.0 | 1232 | 0.0971 | 0.2088 | |
|
|
| 1.0944 | 9.0 | 1386 | 0.0954 | 0.2085 | |
|
|
| 1.032 | 10.0 | 1540 | 0.0956 | 0.2104 | |
|
|
| 0.9384 | 11.0 | 1694 | 0.0948 | 0.2026 | |
|
|
| 0.8799 | 12.0 | 1848 | 0.0942 | 0.2053 | |
|
|
| 0.8374 | 13.0 | 2002 | 0.0939 | 0.2062 | |
|
|
| 0.7891 | 14.0 | 2156 | 0.0940 | 0.2065 | |
|
|
| 0.7622 | 14.9070 | 2295 | 0.0940 | 0.2050 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.1 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.0 |
|
|
|
