metadata

language:
  - sv
license: apache-2.0
tags:
  - i-dont-know-what-im-doing
  - generated_from_trainer
datasets:
  - fimster/NST_small_whisper
metrics:
  - wer
model-index:
  - name: Whisper Small sv-SE NST - Lab 2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NST Swedish ASR
          type: fimster/NST_small_whisper
          config: speech
          split: None
          args: 'config: speech, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 10.167794316644112

Whisper Small sv-SE NST - Lab 2

This model is a fine-tuned version of openai/whisper-small on the NST Swedish ASR dataset. It achieves the following results on the evaluation set:

Loss: 0.1305
Wer: 10.1678

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: 16
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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1635	0.67	1000	0.1694	13.4993
0.07	1.33	2000	0.1431	11.3802
0.0597	2.0	3000	0.1302	10.4682
0.0193	2.67	4000	0.1305	10.1678

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2