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metadata
language:
  - sv
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Small Sv - Riksdag 100h
    results: []

Whisper Small Sv - Riksdag 100h

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4977
  • Wer: 1118.4718

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: 500
  • training_steps: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1384 0.11 1000 0.4747 380.8335
0.1186 0.22 2000 0.4513 1032.3900
0.1056 0.33 3000 0.4385 582.0427
0.0824 0.43 4000 0.4465 574.8907
0.0961 0.54 5000 0.4199 1004.9138
0.0939 0.65 6000 0.4478 866.2979
0.0758 0.76 7000 0.4384 907.9496
0.0741 0.87 8000 0.4264 641.1371
0.0692 0.98 9000 0.4206 1142.6550
0.0257 1.08 10000 0.4707 1152.4312
0.0273 1.19 11000 0.4789 1100.2058
0.021 1.3 12000 0.4763 1236.1719
0.0163 1.41 13000 0.5035 924.8006
0.0183 1.52 14000 0.4911 1285.1814
0.024 1.63 15000 0.4861 1140.8284
0.0158 1.73 16000 0.4793 1181.7597
0.0167 1.84 17000 0.4759 1207.3064
0.0231 1.95 18000 0.4801 1139.6964
0.0054 2.06 19000 0.4934 1114.4842
0.006 2.17 20000 0.4977 1118.4718

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1
  • Datasets 2.10.1
  • Tokenizers 0.13.2