File size: 3,009 Bytes
64b637d 88caac6 64b637d 0348518 64b637d 88caac6 64b637d |
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 81 82 83 84 85 86 87 88 |
---
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: 0.0070
- Wer: 0.0780
- Cer: 0.0312
## 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: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.0099 | 1.0 | 157 | 0.0075 | 0.0746 | 0.0300 |
| 0.0068 | 2.0 | 314 | 0.0069 | 0.0682 | 0.0272 |
| 0.0054 | 3.0 | 471 | 0.0068 | 0.0700 | 0.0278 |
| 0.0043 | 4.0 | 628 | 0.0070 | 0.0726 | 0.0283 |
| 0.0031 | 5.0 | 785 | 0.0074 | 0.0726 | 0.0287 |
| 0.002 | 6.0 | 942 | 0.0082 | 0.0706 | 0.0285 |
| 0.0015 | 7.0 | 1099 | 0.0089 | 0.0758 | 0.0381 |
| 0.0005 | 8.0 | 1256 | 0.0096 | 0.0767 | 0.0479 |
| 0.0001 | 9.0 | 1413 | 0.0100 | 0.0767 | 0.0385 |
| 0.0002 | 10.0 | 1570 | 0.0104 | 0.0746 | 0.0474 |
| 0.0 | 11.0 | 1727 | 0.0107 | 0.0751 | 0.0474 |
| 0.0 | 12.0 | 1884 | 0.0109 | 0.0764 | 0.0482 |
| 0.0 | 13.0 | 2041 | 0.0112 | 0.0746 | 0.0479 |
| 0.0 | 14.0 | 2198 | 0.0113 | 0.0749 | 0.0488 |
| 0.0 | 15.0 | 2355 | 0.0116 | 0.0767 | 0.0495 |
| 0.0 | 16.0 | 2512 | 0.0119 | 0.0764 | 0.0488 |
| 0.0 | 17.0 | 2669 | 0.0121 | 0.0757 | 0.0487 |
| 0.0 | 18.0 | 2826 | 0.0122 | 0.0753 | 0.0489 |
| 0.0 | 19.0 | 2983 | 0.0127 | 0.0766 | 0.0390 |
| 0.0 | 19.8768 | 3120 | 0.0124 | 0.0755 | 0.0493 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|