metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- naijavoices_igbo_100h
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-igbo_naijavoices_100h
results: []
w2v-bert-2.0-igbo_naijavoices_100h
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the NAIJAVOICES_IGBO_100H - NA dataset. It achieves the following results on the evaluation set:
- Loss: 0.3166
- Wer: 0.3077
- Cer: 0.1314
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 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: 250.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.638 | 3.4483 | 1000 | 0.6548 | 0.5546 | 0.2086 |
| 0.4035 | 6.8966 | 2000 | 0.4278 | 0.3949 | 0.1574 |
| 0.5526 | 10.3448 | 3000 | 0.3694 | 0.3530 | 0.1461 |
| 0.305 | 13.7931 | 4000 | 0.3367 | 0.3357 | 0.1392 |
| 0.2602 | 17.2414 | 5000 | 0.3230 | 0.3252 | 0.1366 |
| 0.4161 | 20.6897 | 6000 | 0.3192 | 0.3226 | 0.1360 |
| 0.2367 | 24.1379 | 7000 | 0.3196 | 0.3192 | 0.1345 |
| 0.2463 | 27.5862 | 8000 | 0.3153 | 0.3089 | 0.1324 |
| 0.1819 | 31.0345 | 9000 | 0.3187 | 0.3034 | 0.1334 |
| 0.1852 | 34.4828 | 10000 | 0.3292 | 0.3067 | 0.1326 |
| 0.1581 | 37.9310 | 11000 | 0.3510 | 0.2997 | 0.1310 |
| 0.1455 | 41.3793 | 12000 | 0.3522 | 0.3080 | 0.1348 |
| 0.0998 | 44.8276 | 13000 | 0.3933 | 0.3094 | 0.1373 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2