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whisper-9-dutch

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metadata
language:
  - nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Large V2
    results: []

Whisper Large V2

This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2872
  • Wer: 10.3543

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: 3e-05
  • train_batch_size: 12
  • 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: 20
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer
0.6091 0.09 30 0.3548 15.0266
0.3073 0.19 60 0.3203 13.7016
0.3171 0.28 90 0.3049 12.6189
0.29 0.38 120 0.3033 13.9760
0.2907 0.47 150 0.2824 12.9750
0.2748 0.57 180 0.2737 13.1413
0.2637 0.66 210 0.2655 15.0149
0.2672 0.76 240 0.2629 15.7094
0.2483 0.85 270 0.2616 13.7483
0.2531 0.95 300 0.2603 13.5732
0.1988 1.04 330 0.2713 12.3417
0.1271 1.14 360 0.2644 12.3942
0.1309 1.23 390 0.2612 12.6218
0.1506 1.33 420 0.2633 17.3204
0.1365 1.42 450 0.2621 13.2551
0.1379 1.52 480 0.2636 13.2901
0.1325 1.61 510 0.2550 12.8845
0.129 1.71 540 0.2575 14.0139
0.1334 1.8 570 0.2513 12.2104
0.1418 1.9 600 0.2484 12.2541
0.1438 1.99 630 0.2457 12.0119
0.0651 2.09 660 0.2646 12.3358
0.0649 2.18 690 0.2684 10.6286
0.0638 2.28 720 0.2645 11.6121
0.0651 2.37 750 0.2616 11.4020
0.0656 2.47 780 0.2574 11.4457
0.0643 2.56 810 0.2592 11.7113
0.0682 2.66 840 0.2597 11.5625
0.0583 2.75 870 0.2571 12.9020
0.0608 2.85 900 0.2574 14.3991
0.064 2.94 930 0.2535 10.6023
0.0429 3.04 960 0.2648 10.9788
0.0264 3.13 990 0.2710 10.3514
0.0251 3.23 1020 0.2688 10.4302
0.0244 3.32 1050 0.2709 9.9778
0.0251 3.42 1080 0.2732 10.1733
0.0245 3.51 1110 0.2720 11.1043
0.0246 3.61 1140 0.2765 10.8446
0.0254 3.7 1170 0.2709 10.7658
0.0234 3.8 1200 0.2663 10.3485
0.022 3.89 1230 0.2649 11.4370
0.0237 3.99 1260 0.2688 11.0138
0.011 4.08 1290 0.2791 10.3076
0.0107 4.18 1320 0.2839 10.4798
0.0087 4.27 1350 0.2871 10.4856
0.0081 4.37 1380 0.2894 10.3280
0.0094 4.46 1410 0.2872 10.2259
0.0083 4.56 1440 0.2887 10.2288
0.0104 4.65 1470 0.2856 10.2638
0.009 4.75 1500 0.2855 10.3339
0.0068 4.84 1530 0.2865 10.4010
0.0082 4.94 1560 0.2872 10.3543

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.0