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whisper-small-ft-malay-peft-epoch-20

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metadata
library_name: peft
language:
  - ms
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - clt013/malay-speech-3k-rows-dataset_v2
model-index:
  - name: Whisper Small FT Malay - CLT013
    results: []

Whisper Small FT Malay - CLT013

This model is a fine-tuned version of openai/whisper-small on the Malay Speech 3k dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8613

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: 0.001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.1842 0.3731 100 0.8172
0.7488 0.7463 200 0.8014
0.6424 1.1194 300 0.8136
0.5234 1.4925 400 0.7511
0.4951 1.8657 500 0.8203
0.3835 2.2388 600 0.8191
0.3519 2.6119 700 0.8001
0.3868 2.9851 800 0.8011
0.2568 3.3582 900 0.8630
0.2781 3.7313 1000 0.8269
0.2535 4.1045 1100 0.8612
0.2105 4.4776 1200 0.8486
0.2104 4.8507 1300 0.8367
0.1726 5.2239 1400 0.8692
0.1672 5.5970 1500 0.8483
0.1641 5.9701 1600 0.8443
0.1186 6.3433 1700 0.9531
0.1261 6.7164 1800 0.8578
0.1211 7.0896 1900 0.8922
0.0962 7.4627 2000 0.9107
0.1188 7.8358 2100 0.8498
0.0847 8.2090 2200 0.8554
0.0802 8.5821 2300 0.9024
0.0805 8.9552 2400 0.8649
0.0559 9.3284 2500 0.8634
0.053 9.7015 2600 0.8988
0.0555 10.0746 2700 0.8657
0.0415 10.4478 2800 0.8449
0.0401 10.8209 2900 0.8658
0.0318 11.1940 3000 0.8674
0.0245 11.5672 3100 0.8491
0.032 11.9403 3200 0.8694
0.0186 12.3134 3300 0.8620
0.0179 12.6866 3400 0.8555
0.015 13.0597 3500 0.8730
0.0176 13.4328 3600 0.8458
0.0155 13.8060 3700 0.8454
0.0121 14.1791 3800 0.8533
0.0139 14.5522 3900 0.8604
0.009 14.9254 4000 0.8676
0.0095 15.2985 4100 0.8649
0.0059 15.6716 4200 0.8728
0.0065 16.0448 4300 0.8570
0.0049 16.4179 4400 0.8521
0.0042 16.7910 4500 0.8600
0.0051 17.1642 4600 0.8741
0.0037 17.5373 4700 0.8666
0.0037 17.9104 4800 0.8691
0.0029 18.2836 4900 0.8619
0.0023 18.6567 5000 0.8603
0.0019 19.0299 5100 0.8629
0.0018 19.4030 5200 0.8608
0.0018 19.7761 5300 0.8613

Framework versions

  • PEFT 0.13.2
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1