---
library_name: transformers
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-yoruba_naijavoices_1m
  results: []
license: mit
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-2.0-yoruba_naijavoices_1m

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4581
- Wer: 1.1091
- Cer: 0.7667

## 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: 3e-05
- train_batch_size: 160
- eval_batch_size: 160
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 320
- optimizer: Use OptimizerNames.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_ratio: 0.1
- num_epochs: 1500000.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.234         | 100.0  | 100  | 6.7307          | 1.0096 | 1.6670 |
| 3.1973        | 200.0  | 200  | 6.6276          | 1.0370 | 1.6333 |
| 3.0872        | 300.0  | 300  | 6.4408          | 1.1971 | 1.5514 |
| 2.9384        | 400.0  | 400  | 6.1546          | 1.5313 | 1.3571 |
| 2.7071        | 500.0  | 500  | 5.6664          | 1.4447 | 0.9348 |
| 2.4205        | 600.0  | 600  | 5.0371          | 1.0002 | 0.8403 |
| 2.0893        | 700.0  | 700  | 4.2922          | 0.9999 | 0.9857 |
| 1.7985        | 800.0  | 800  | 3.6646          | 1.0    | 0.9999 |
| 1.6823        | 900.0  | 900  | 3.5062          | 1.0    | 0.9997 |
| 1.595         | 1000.0 | 1000 | 3.4488          | 1.0    | 0.9977 |
| 1.5454        | 1100.0 | 1100 | 3.4338          | 0.9997 | 0.9915 |
| 1.4837        | 1200.0 | 1200 | 3.4315          | 0.9997 | 0.9775 |
| 1.4207        | 1300.0 | 1300 | 3.4209          | 0.9997 | 0.9656 |
| 1.3568        | 1400.0 | 1400 | 3.4141          | 0.9992 | 0.9433 |
| 1.3063        | 1500.0 | 1500 | 3.4006          | 0.9989 | 0.9278 |
| 1.2384        | 1600.0 | 1600 | 3.3922          | 0.9983 | 0.8960 |
| 1.1702        | 1700.0 | 1700 | 3.3778          | 0.9985 | 0.8699 |
| 1.1001        | 1800.0 | 1800 | 3.3645          | 1.0016 | 0.8490 |
| 1.0239        | 1900.0 | 1900 | 3.3482          | 1.0068 | 0.8273 |
| 0.9399        | 2000.0 | 2000 | 3.3392          | 1.0146 | 0.8053 |
| 0.8678        | 2100.0 | 2100 | 3.3164          | 1.0220 | 0.7927 |
| 0.7737        | 2200.0 | 2200 | 3.3033          | 1.0366 | 0.7796 |
| 0.6932        | 2300.0 | 2300 | 3.2972          | 1.0560 | 0.7657 |
| 0.5941        | 2400.0 | 2400 | 3.2959          | 1.0712 | 0.7593 |
| 0.5273        | 2500.0 | 2500 | 3.3100          | 1.0842 | 0.7555 |
| 0.4467        | 2600.0 | 2600 | 3.3402          | 1.0937 | 0.7558 |
| 0.3664        | 2700.0 | 2700 | 3.3720          | 1.0987 | 0.7584 |
| 0.2973        | 2800.0 | 2800 | 3.4065          | 1.1081 | 0.7594 |
| 0.2244        | 2900.0 | 2900 | 3.4581          | 1.1091 | 0.7667 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2