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asr-shikomori-swahili – AI Model by rifailabs | AlphaNeural AI
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asr-shikomori-swahili
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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asr-shikomori-swahili
This model is a fine-tuned version of
openai/whisper-small
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 0.8698
eval_wer: 39.5001
eval_cer: 13.7566
eval_runtime: 511.342
eval_samples_per_second: 1.862
eval_steps_per_second: 0.233
epoch: 14.7059
step: 3500
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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 8000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.19.1
