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---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- CLEAR-Global/naijavoices_100h
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-hausa_naijavoices_100h
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. -->
# w2v-bert-2.0-hausa_naijavoices_100h
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the CLEAR-GLOBAL/NAIJAVOICES_100H - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2644
- Wer: 0.3398
- Cer: 0.1916
## 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
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 320
- total_eval_batch_size: 320
- 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_ratio: 0.1
- num_epochs: 250.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 0.346 | 2.7933 | 1000 | 0.4367 | 0.4197 | 0.2131 |
| 0.2972 | 5.5866 | 2000 | 0.3150 | 0.3691 | 0.1998 |
| 0.2638 | 8.3799 | 3000 | 0.2892 | 0.3556 | 0.1959 |
| 0.2308 | 11.1732 | 4000 | 0.2728 | 0.3471 | 0.1938 |
| 0.2338 | 13.9665 | 5000 | 0.2707 | 0.3430 | 0.1929 |
| 0.2105 | 16.7598 | 6000 | 0.2687 | 0.3389 | 0.1917 |
| 0.1732 | 19.5531 | 7000 | 0.2710 | 0.3437 | 0.1935 |
| 0.1638 | 22.3464 | 8000 | 0.2657 | 0.3426 | 0.1927 |
| 0.1933 | 25.1397 | 9000 | 0.2787 | 0.3413 | 0.1918 |
| 0.144 | 27.9330 | 10000 | 0.2651 | 0.3397 | 0.1916 |
| 0.1493 | 30.7263 | 11000 | 0.2757 | 0.3415 | 0.1923 |
| 0.1267 | 33.5196 | 12000 | 0.2826 | 0.3482 | 0.1924 |
| 0.1045 | 36.3128 | 13000 | 0.3057 | 0.3480 | 0.1930 |
| 0.066 | 39.1061 | 14000 | 0.3314 | 0.3526 | 0.1942 |
| 0.0564 | 41.8994 | 15000 | 0.3840 | 0.3541 | 0.1939 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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