whisper-small-ne-en-finetuned – AI Model by Bijay13 | AlphaNeural AI

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Bijay13/
whisper-small-ne-en-finetuned

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automatic-speech-recognition

generated_from_trainer

openai/whisper-small

endpoints_compatible

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whisper-small-ne-en-finetuned

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2826
Wer: 48.5469

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
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: 500
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7411	0.4987	190	0.7084	77.2690
0.4667	0.9974	380	0.4530	59.3461
0.3134	1.4961	570	0.3336	53.0903
0.2698	1.9948	760	0.2922	50.0471
0.204	2.4934	950	0.2811	48.4046
0.1924	2.9921	1140	0.2744	47.9273

Framework versions

Transformers 4.57.3
Pytorch 2.9.1+cu128
Datasets 2.21.0
Tokenizers 0.22.1