whisper-base-ne – AI Model by kiranpantha | AlphaNeural AI

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kiranpantha/
whisper-base-ne

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automatic-speech-recognition

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openslr/openslr

openai/whisper-base

endpoints_compatible

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Whisper Base - Kiran Pantha

This model is a fine-tuned version of openai/whisper-base on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

Loss: 0.2056
Wer: 43.2821

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: 4
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: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5029	0.0750	500	0.4922	77.0205
0.351	0.1499	1000	0.3561	65.6941
0.3034	0.2249	1500	0.2988	57.0618
0.2689	0.2999	2000	0.2714	53.2844
0.2584	0.3749	2500	0.2537	50.8369
0.2325	0.4498	3000	0.2393	48.0282
0.2238	0.5248	3500	0.2271	46.5723
0.2149	0.5998	4000	0.2149	44.4056
0.2038	0.6748	4500	0.2091	43.6834
0.2026	0.7497	5000	0.2056	43.2821

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1