Edit model card

finetuning-wav2vec-large-swahili-asr-model_v19

This model is a fine-tuned version of Joshua-Abok/finetuning-wav2vec-large-swahili-asr-model_v10 on the fleurs dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.3234
  • eval_wer: 0.9985
  • eval_runtime: 63.1279
  • eval_samples_per_second: 7.714
  • eval_steps_per_second: 0.966
  • epoch: 9.73
  • step: 2000

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.7
  • Tokenizers 0.14.1
Downloads last month
2
Safetensors
Model size
315M params
Tensor type
F32
·
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Finetuned from