metadata
library_name: transformers
language:
- yo
- en
- ig
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
model-index:
- name: whisper-small-multilingual-naija-11-03-2024
results: []
whisper-small-multilingual-naija-11-03-2024
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8445
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 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: 1.5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.926 | 0.0296 | 100 | 2.1605 |
| 2.1251 | 0.0592 | 200 | 1.6041 |
| 1.8711 | 0.0889 | 300 | 1.3987 |
| 1.5748 | 0.1185 | 400 | 1.2746 |
| 1.4264 | 0.1481 | 500 | 1.2025 |
| 1.4298 | 0.1777 | 600 | 1.1450 |
| 1.3167 | 0.2073 | 700 | 1.0946 |
| 1.2684 | 0.2370 | 800 | 1.0631 |
| 1.1892 | 0.2666 | 900 | 1.0364 |
| 1.16 | 0.2962 | 1000 | 1.0220 |
| 1.1475 | 0.3258 | 1100 | 1.0080 |
| 1.0742 | 0.3555 | 1200 | 0.9798 |
| 1.066 | 0.3851 | 1300 | 0.9837 |
| 1.0404 | 0.4147 | 1400 | 0.9693 |
| 1.055 | 0.4443 | 1500 | 0.9536 |
| 1.0622 | 0.4739 | 1600 | 0.9489 |
| 0.9947 | 0.5036 | 1700 | 0.9403 |
| 0.9904 | 0.5332 | 1800 | 0.9300 |
| 0.9607 | 0.5628 | 1900 | 0.9207 |
| 0.9464 | 0.5924 | 2000 | 0.9250 |
| 0.9086 | 0.6220 | 2100 | 0.9131 |
| 0.9332 | 0.6517 | 2200 | 0.8991 |
| 0.8954 | 0.6813 | 2300 | 0.8989 |
| 0.9175 | 0.7109 | 2400 | 0.8899 |
| 0.9203 | 0.7405 | 2500 | 0.8886 |
| 0.84 | 0.7701 | 2600 | 0.8874 |
| 0.8379 | 0.7998 | 2700 | 0.8796 |
| 0.8328 | 0.8294 | 2800 | 0.8765 |
| 0.8455 | 0.8590 | 2900 | 0.8671 |
| 0.8391 | 0.8886 | 3000 | 0.8622 |
| 0.7729 | 0.9182 | 3100 | 0.8699 |
| 0.803 | 0.9479 | 3200 | 0.8597 |
| 0.7808 | 0.9775 | 3300 | 0.8507 |
| 0.729 | 1.0071 | 3400 | 0.8573 |
| 0.7048 | 1.0367 | 3500 | 0.8581 |
| 0.7018 | 1.0664 | 3600 | 0.8551 |
| 0.7297 | 1.0960 | 3700 | 0.8545 |
| 0.6594 | 1.1256 | 3800 | 0.8504 |
| 0.6682 | 1.1552 | 3900 | 0.8566 |
| 0.6621 | 1.1848 | 4000 | 0.8548 |
| 0.6626 | 1.2145 | 4100 | 0.8510 |
| 0.6611 | 1.2441 | 4200 | 0.8493 |
| 0.6505 | 1.2737 | 4300 | 0.8464 |
| 0.6323 | 1.3033 | 4400 | 0.8483 |
| 0.6564 | 1.3329 | 4500 | 0.8421 |
| 0.6293 | 1.3626 | 4600 | 0.8454 |
| 0.5936 | 1.3922 | 4700 | 0.8447 |
| 0.6114 | 1.4218 | 4800 | 0.8458 |
| 0.6551 | 1.4514 | 4900 | 0.8454 |
| 0.5963 | 1.4810 | 5000 | 0.8445 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1