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finetuning-wav2vec-large-swahili-asr-model_v9 – AI Model by Joshua-Abok | AlphaNeural AI

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Joshua-Abok/
finetuning-wav2vec-large-swahili-asr-model_v9

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automatic-speech-recognition

generated_from_trainer

common_voice_13_0

AntonyG/fine-tune-wav2vec2-large-xls-r-1b-sw

endpoints_compatible

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finetuning-wav2vec-large-swahili-asr-model_v9

This model is a fine-tuned version of AntonyG/fine-tune-wav2vec2-large-xls-r-1b-sw on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.3804
eval_wer: 0.2066
eval_runtime: 611.206
eval_samples_per_second: 18.441
eval_steps_per_second: 2.305
epoch: 0.28
step: 400

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: 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: 15
mixed_precision_training: Native AMP

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.6
Tokenizers 0.14.1