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whisper-8-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: 0.2674
  • Wer: 8.9178

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
0.5984 0.09 30 0.3391 13.4234
0.3844 0.19 60 0.2936 16.0882
0.3245 0.28 90 0.2801 12.7436
0.2967 0.38 120 0.2602 12.8549
0.2526 0.47 150 0.2604 17.7364
0.2889 0.57 180 0.2466 13.2940
0.2378 0.66 210 0.2506 15.9919
0.237 0.76 240 0.2500 17.4176
0.2769 0.85 270 0.2340 15.0956
0.2579 0.95 300 0.2365 13.3482
0.1979 1.04 330 0.2461 15.3333
0.1336 1.14 360 0.2416 13.3331
0.1415 1.23 390 0.2380 14.3918
0.1307 1.33 420 0.2397 11.2879
0.1489 1.42 450 0.2389 11.0954
0.1311 1.52 480 0.2378 14.1783
0.1256 1.61 510 0.2333 12.2895
0.1283 1.71 540 0.2318 10.5901
0.1418 1.8 570 0.2317 14.6084
0.1346 1.9 600 0.2284 12.2564
0.1357 1.99 630 0.2212 10.5029
0.0641 2.09 660 0.2369 11.4894
0.0587 2.18 690 0.2383 9.7690
0.0585 2.28 720 0.2378 11.6037
0.0601 2.37 750 0.2409 11.6609
0.0645 2.47 780 0.2397 10.4397
0.0648 2.56 810 0.2430 10.2984
0.0616 2.66 840 0.2421 10.3946
0.0668 2.75 870 0.2351 13.2489
0.0553 2.85 900 0.2343 10.6563
0.0576 2.94 930 0.2359 10.2262
0.0468 3.04 960 0.2433 10.1329
0.0253 3.13 990 0.2496 10.0638
0.025 3.23 1020 0.2480 11.0864
0.0232 3.32 1050 0.2550 9.9916
0.0252 3.42 1080 0.2531 9.3269
0.0254 3.51 1110 0.2472 9.0381
0.0225 3.61 1140 0.2549 9.2908
0.0218 3.7 1170 0.2496 9.5404
0.0242 3.8 1200 0.2432 9.9284
0.0223 3.89 1230 0.2462 10.8277
0.0204 3.99 1260 0.2522 9.6637
0.0115 4.08 1290 0.2585 8.8426
0.0094 4.18 1320 0.2622 9.4923
0.0092 4.27 1350 0.2638 10.6773
0.009 4.37 1380 0.2640 10.0999
0.009 4.46 1410 0.2664 10.0036
0.0087 4.56 1440 0.2666 9.9705
0.0075 4.65 1470 0.2672 9.8622
0.0077 4.75 1500 0.2658 9.1254
0.0069 4.84 1530 0.2667 9.0442
0.0081 4.94 1560 0.2674 8.9178

Framework versions

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