This model is a fine-tuned version of facebook/w2v-bert-2.0 on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

Loss: 0.8937
Wer: 0.6454

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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.1352	4.62	300	0.9144	0.7024
0.5115	9.23	600	0.8937	0.6454

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

oyemade/w2v-bert-2.0-yoruba-colab-CV16.1

w2v-bert-2.0-yoruba-colab-CV16.1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

oyemade/
w2v-bert-2.0-yoruba-colab-CV16.1