Edit model card

Whisper Large v3 Fine-Tuned Finnish - CommonVoice13

This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3976
  • Wer: 21.4246

It achieves the following results on the Test set:

  • Eval_Wer: 21.378612184796612
  • Eval_NormalizedWer: 18.415004137170175

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
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • training_steps: 800
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0001 0.84 50 0.4009 21.6363
0.0013 1.68 100 0.3801 22.5014
0.0013 2.53 150 0.3852 23.2192
0.0009 3.37 200 0.3738 23.1824
0.0007 4.21 250 0.3697 23.2100
0.0001 5.05 300 0.3777 21.9032
0.0001 5.89 350 0.3825 21.8388
0.0001 6.74 400 0.3864 21.7651
0.0 7.58 450 0.3895 21.6455
0.0 8.42 500 0.3917 21.5351
0.0 9.26 550 0.3936 21.4983
0.0 10.11 600 0.3951 21.4338
0.0 10.95 650 0.3962 21.4338
0.0 11.79 700 0.3970 21.4614
0.0 12.63 750 0.3975 21.4338
0.0 13.47 800 0.3976 21.4246

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.16.1
  • Tokenizers 0.15.0
Downloads last month
2
Safetensors
Model size
1.54B params
Tensor type
F32
·

Finetuned from