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1from datasets import Audio, load_dataset
2from transformers import pipeline
3
4# Load a sample audio
5dataset = load_dataset("chuuhtetnaing/myanmar-speech-dataset-openslr-80")
6dataset = dataset.cast_column("audio", Audio(sampling_rate=16000))
7test_dataset = dataset['test']
8input_speech = test_dataset[42]['audio']
9
10pipe = pipeline(model='chuuhtetnaing/whisper-tiny-myanmar')
11
12output = pipe(input_speech, generate_kwargs={"language": "myanmar", "task": "transcribe"})
13print(output['text']) # ကျွန်မ ပြည်ပ မှာ ပညာ သင် တော့ စာမြီးပွဲ ကို တပတ်တခါ စစ်တယ်| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 1.0 | 18 | 1.2679 | 357.6135 |
| 1.483 | 2.0 | 36 | 1.0660 | 102.5378 |
| 1.0703 | 3.0 | 54 | 0.9530 | 106.3669 |
| 1.0703 | 4.0 | 72 | 0.8399 | 100.5343 |
| 0.8951 | 5.0 | 90 | 0.7728 | 107.6581 |
| 0.7857 | 6.0 | 108 | 0.7143 | 107.5245 |
| 0.6614 | 7.0 | 126 | 0.5174 | 104.4078 |
| 0.6614 | 8.0 | 144 | 0.3004 | 90.3384 |
| 0.3519 | 9.0 | 162 | 0.2447 | 82.4577 |
| 0.2165 | 10.0 | 180 | 0.2333 | 83.8825 |
| 0.2165 | 11.0 | 198 | 0.2022 | 77.0258 |
| 0.1532 | 12.0 | 216 | 0.1759 | 73.0632 |
| 0.1039 | 13.0 | 234 | 0.1852 | 72.0837 |
| 0.0675 | 14.0 | 252 | 0.1902 | 71.2823 |
| 0.0675 | 15.0 | 270 | 0.1882 | 70.5254 |
| 0.0517 | 16.0 | 288 | 0.2002 | 69.7240 |
| 0.0522 | 17.0 | 306 | 0.1965 | 67.7649 |
| 0.0522 | 18.0 | 324 | 0.1935 | 68.2102 |
| 0.0404 | 19.0 | 342 | 0.2132 | 67.9430 |
| 0.0308 | 20.0 | 360 | 0.2110 | 66.6963 |
| 0.0236 | 21.0 | 378 | 0.2141 | 65.9394 |
| 0.0236 | 22.0 | 396 | 0.2200 | 64.4702 |
| 0.0116 | 23.0 | 414 | 0.2227 | 63.4016 |
| 0.0055 | 24.0 | 432 | 0.2244 | 64.1585 |
| 0.0025 | 25.0 | 450 | 0.2254 | 62.4666 |
| 0.0025 | 26.0 | 468 | 0.2282 | 63.1790 |
| 0.0006 | 27.0 | 486 | 0.2320 | 61.7097 |
| 0.0002 | 28.0 | 504 | 0.2342 | 62.0659 |
| 0.0002 | 29.0 | 522 | 0.2350 | 62.0214 |
| 0.0001 | 30.0 | 540 | 0.2353 | 61.8878 |