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finetuning-whisper-small-swahili-ablation_ndizi_FLEURS – AI Model by smutuvi | AlphaNeural AI
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smutuvi
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finetuning-whisper-small-swahili-ablation_ndizi_FLEURS
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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finetuning-whisper-small-swahili-ablation_ndizi_FLEURS
This model is a fine-tuned version of
openai/whisper-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.8979
Wer: 51.6422
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: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.6343
2.1369
1000
0.8026
53.0525
0.4098
4.2738
2000
0.8010
52.1213
0.2735
6.4107
3000
0.8608
52.8648
0.2033
8.5476
4000
0.8979
51.6422
Framework versions
Transformers 4.57.1
Pytorch 2.9.0+cu128
Datasets 3.6.0
Tokenizers 0.22.1
