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---
library_name: transformers
language:
- yo
- en
- ig
license: apache-2.0
base_model: ccibeekeoc42/whisper-small-yoruba-07-17
tags:
- generated_from_trainer
model-index:
- name: whisper-small-multilingual-naija-10-25-2024
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-small-multilingual-naija-10-25-2024
This model is a fine-tuned version of [ccibeekeoc42/whisper-small-yoruba-07-17](https://huggingface.co./ccibeekeoc42/whisper-small-yoruba-07-17) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7577
## 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9909 | 0.0229 | 100 | 1.5086 |
| 1.6658 | 0.0457 | 200 | 1.1909 |
| 1.421 | 0.0686 | 300 | 1.0778 |
| 1.3603 | 0.0914 | 400 | 1.0138 |
| 1.3567 | 0.1143 | 500 | 0.9721 |
| 1.2484 | 0.1372 | 600 | 0.9448 |
| 1.1076 | 0.1600 | 700 | 0.9270 |
| 1.0729 | 0.1829 | 800 | 0.9088 |
| 1.042 | 0.2058 | 900 | 0.8900 |
| 1.0528 | 0.2286 | 1000 | 0.8817 |
| 1.0261 | 0.2515 | 1100 | 0.8674 |
| 0.9289 | 0.2743 | 1200 | 0.8631 |
| 0.959 | 0.2972 | 1300 | 0.8460 |
| 0.9355 | 0.3201 | 1400 | 0.8436 |
| 0.9855 | 0.3429 | 1500 | 0.8351 |
| 0.9426 | 0.3658 | 1600 | 0.8291 |
| 0.8913 | 0.3887 | 1700 | 0.8233 |
| 0.9202 | 0.4115 | 1800 | 0.8180 |
| 0.9122 | 0.4344 | 1900 | 0.8131 |
| 0.8454 | 0.4572 | 2000 | 0.8104 |
| 0.8048 | 0.4801 | 2100 | 0.8074 |
| 0.8824 | 0.5030 | 2200 | 0.8006 |
| 0.8707 | 0.5258 | 2300 | 0.7965 |
| 0.8955 | 0.5487 | 2400 | 0.7941 |
| 0.8237 | 0.5716 | 2500 | 0.7940 |
| 0.8774 | 0.5944 | 2600 | 0.7921 |
| 0.8162 | 0.6173 | 2700 | 0.7836 |
| 0.8308 | 0.6401 | 2800 | 0.7829 |
| 0.7863 | 0.6630 | 2900 | 0.7786 |
| 0.7536 | 0.6859 | 3000 | 0.7744 |
| 0.8215 | 0.7087 | 3100 | 0.7730 |
| 0.7852 | 0.7316 | 3200 | 0.7709 |
| 0.7569 | 0.7545 | 3300 | 0.7699 |
| 0.7298 | 0.7773 | 3400 | 0.7685 |
| 0.7777 | 0.8002 | 3500 | 0.7659 |
| 0.7358 | 0.8230 | 3600 | 0.7637 |
| 0.7258 | 0.8459 | 3700 | 0.7611 |
| 0.7674 | 0.8688 | 3800 | 0.7604 |
| 0.8048 | 0.8916 | 3900 | 0.7599 |
| 0.7694 | 0.9145 | 4000 | 0.7590 |
| 0.8072 | 0.9374 | 4100 | 0.7577 |
| 0.7765 | 0.9602 | 4200 | 0.7580 |
| 0.7789 | 0.9831 | 4300 | 0.7577 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.0.1+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1
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