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whisper-large-v3-ft-malay-peft-v1

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metadata
base_model: openai/whisper-large-v3
datasets:
  - clt013/malay-speech-3k-rows-dataset_v2
language:
  - ms
library_name: peft
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: Whisper Large v3 FT Malay - CLT013
    results: []

Whisper Large v3 FT Malay - CLT013

This model is a fine-tuned version of openai/whisper-large-v3 on the Malay Speech 3k dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7194

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.5614 0.0933 25 2.6198
2.9109 0.1866 50 2.5967
2.5414 0.2799 75 2.5518
2.4919 0.3731 100 2.4742
2.5861 0.4664 125 2.3639
2.454 0.5597 150 2.2213
2.32 0.6530 175 2.0616
2.1081 0.7463 200 1.8668
1.7976 0.8396 225 1.6736
1.7597 0.9328 250 1.5280
1.469 1.0261 275 1.4172
1.4484 1.1194 300 1.3275
1.2641 1.2127 325 1.2592
1.1853 1.3060 350 1.1972
1.184 1.3993 375 1.1449
1.1733 1.4925 400 1.0964
1.0707 1.5858 425 1.0568
0.9975 1.6791 450 1.0172
0.9897 1.7724 475 0.9855
1.0223 1.8657 500 0.9524
0.875 1.9590 525 0.9232
0.9242 2.0522 550 0.8968
0.8829 2.1455 575 0.8709
0.8491 2.2388 600 0.8454
0.7793 2.3321 625 0.8236
0.7733 2.4254 650 0.7993
0.7085 2.5187 675 0.7787
0.7403 2.6119 700 0.7596
0.7019 2.7052 725 0.7415
0.722 2.7985 750 0.7309
0.6403 2.8918 775 0.7220
0.699 2.9851 800 0.7194

Framework versions

  • PEFT 0.13.0
  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1