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SPEAK-ASR/
whisper-si-exp-10

Name: whisper-si-exp-10
Availability: InStock

SPEAK-ASR/openslr-sinhala-asr-norm-noise-rem-preprocessed

openai/whisper-small

apache-2.0

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SPEAK-ASR/whisper-si-exp-10

This model is a fine-tuned version of openai/whisper-small on the SPEAK-ASR/openslr-sinhala-asr-norm-noise-rem-preprocessed dataset. It achieves the following results on the evaluation set:

Loss: 0.1739
Wer: 12.6991

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: 0.0006926233815806411
train_batch_size: 128
eval_batch_size: 256
seed: 42
optimizer: Use 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: 295
num_epochs: 20.0

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2032	1.0	473	0.1951	22.2112
0.1473	2.0	946	0.1551	18.1276
0.1243	3.0	1419	0.1471	16.4627
0.1083	4.0	1892	0.1319	14.6748
0.0976	5.0	2365	0.1371	15.8588
0.0883	6.0	2838	0.1271	14.3492
0.0823	7.0	3311	0.1247	13.4447
0.0738	8.0	3784	0.1311	13.9303
0.0675	9.0	4257	0.1251	13.3315
0.0602	10.0	4730	0.1254	13.0560
0.0534	11.0	5203	0.1285	12.9820
0.0466	12.0	5676	0.1330	12.8602
0.0395	13.0	6149	0.1382	13.2603
0.0350	14.0	6622	0.1410	12.7947
0.0282	15.0	7095	0.1477	12.6035
0.0228	16.0	7568	0.1557	12.7520
0.0176	17.0	8041	0.1637	12.7514
0.0137	18.0	8514	0.1739	12.6991

Framework versions

PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.9.0.dev20250821+rocm7.0.0.git125803b7
Datasets 4.5.0
Tokenizers 0.22.2