---
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