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---
base_model: oyemade/w2v-bert-2.0-yoruba-CV17.0
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: w2v-bert-2.0-yoruba-CV17.0
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: yo
split: test
args: yo
metrics:
- name: Wer
type: wer
value: 0.10649647551914651
language:
- yo
---
<!-- 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-yoruba-CV17.0
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1095
- Wer: 0.1065
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 6
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.3812 | 0.5102 | 100 | 0.3328 | 0.3070 |
| 0.2283 | 1.0204 | 200 | 0.2721 | 0.2807 |
| 0.1993 | 1.5306 | 300 | 0.3371 | 0.3481 |
| 0.2045 | 2.0408 | 400 | 0.3514 | 0.3314 |
| 0.2057 | 2.5510 | 500 | 0.3036 | 0.3086 |
| 0.2193 | 3.0612 | 600 | 0.2904 | 0.2847 |
| 0.1956 | 3.5714 | 700 | 0.2631 | 0.2534 |
| 0.1717 | 4.0816 | 800 | 0.1923 | 0.1995 |
| 0.1234 | 4.5918 | 900 | 0.1678 | 0.1732 |
| 0.0995 | 5.1020 | 1000 | 0.1280 | 0.1341 |
| 0.0614 | 5.6122 | 1100 | 0.1095 | 0.1065 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |