File size: 2,413 Bytes
07d9105 bf3ec06 07d9105 bf3ec06 07d9105 bf3ec06 07d9105 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
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: []
---
<!-- 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 tiny AR - BH
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the quran-ayat-speech-to-text dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0191
- Wer: 0.1462
- Cer: 0.0494
## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0148 | 1.0 | 250 | 0.0146 | 0.1685 | 0.0520 |
| 0.0109 | 2.0 | 500 | 0.0144 | 0.1765 | 0.0595 |
| 0.0082 | 3.0 | 750 | 0.0152 | 0.1634 | 0.0542 |
| 0.0065 | 4.0 | 1000 | 0.0155 | 0.1593 | 0.0505 |
| 0.0033 | 5.0 | 1250 | 0.0181 | 0.1644 | 0.0571 |
| 0.0025 | 6.0 | 1500 | 0.0182 | 0.1558 | 0.0533 |
| 0.0024 | 7.0 | 1750 | 0.0180 | 0.1544 | 0.0492 |
| 0.0014 | 8.0 | 2000 | 0.0190 | 0.1461 | 0.0508 |
| 0.001 | 9.0 | 2250 | 0.0196 | 0.1430 | 0.0479 |
| 0.0006 | 10.0 | 2500 | 0.0198 | 0.1467 | 0.0497 |
| 0.0005 | 11.0 | 2750 | 0.0198 | 0.1531 | 0.0503 |
| 0.0004 | 12.0 | 3000 | 0.0197 | 0.1446 | 0.0473 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|