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whisper-tiny-minds14

This model is a fine-tuned version of openai/whisper-tiny on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7473
  • Wer Ortho: 0.2788
  • Wer: 0.2834

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: 3.220378398329722e-05
  • train_batch_size: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9850038588304092,0.9902432649395926) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 205
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
No log 1.0 28 2.9124 0.5305 0.3991
No log 2.0 56 1.3721 0.4516 0.4091
No log 3.0 84 0.6397 0.3856 0.3872
No log 4.0 112 0.5424 0.3849 0.3819
No log 5.0 140 0.5124 0.4460 0.4410
No log 6.0 168 0.5153 0.3479 0.3477
No log 7.0 196 0.5565 0.3418 0.3424
No log 8.0 224 0.5882 0.3208 0.3229
No log 9.0 252 0.6248 0.3356 0.3371
No log 10.0 280 0.6545 0.3282 0.3300
No log 11.0 308 0.7122 0.3060 0.3093
No log 12.0 336 0.7473 0.2788 0.2834
No log 13.0 364 0.7717 0.3072 0.3093
No log 14.0 392 0.7852 0.3424 0.3447
No log 15.0 420 0.8127 0.3307 0.3318
No log 16.0 448 0.8471 0.3300 0.3294
No log 17.0 476 0.8614 0.3405 0.3406
0.4338 18.0 504 0.8992 0.3627 0.3630
0.4338 19.0 532 0.9157 0.3640 0.3648
0.4338 20.0 560 0.9274 0.3578 0.3589
0.4338 21.0 588 0.9275 0.3387 0.3377
0.4338 22.0 616 0.9371 0.3381 0.3371

Framework versions

  • Transformers 4.32.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.13.2.dev1
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train catactivationsound/whisper-tiny-minds14

Evaluation results