Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
swahili-w2v-bert – AI Model by sitwala | AlphaNeural AI
You can deploy this model and start earning money today!
sitwala
/
swahili-w2v-bert
like
0
transformers
tensorboard
safetensors
wav2vec2-bert
automatic-speech-recognition
generated_from_trainer
facebook/w2v-bert-2.0
finetune
mit
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
Visualize in Weights & Biases
swahili-w2v-bert
This model is a fine-tuned version of
facebook/w2v-bert-2.0
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: inf
Wer: 0.2038
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: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
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_steps: 100
training_steps: 2500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.4225
0.2
500
inf
0.2852
0.307
0.4
1000
inf
0.2363
0.3984
0.6
1500
inf
0.2235
0.1242
0.8
2000
inf
0.2093
0.0832
1.0
2500
inf
0.2038
Framework versions
Transformers 4.52.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
