metadata

language:
  - sv
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
datasets:
  - jimregan/sbtal_riksdag_asr
model-index:
  - name: Whisper Small Sv - Riksdag 100h
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: SBTal Riksdag ASR
          type: jimregan/sbtal_riksdag_asr
        metrics:
          - name: Test WER
            type: wer
            value: 720.3756

Whisper Small Sv - Riksdag 100h

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

Loss: 0.4019
Wer: 720.3756

That's not an error, the results really are that bad, and this should not be used by anyone, ever, except to get a good laugh. I'll try to run fine-tuning again, but don't hold your breath.

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1349	0.11	1000	0.4679	732.5701
0.1071	0.22	2000	0.4305	1417.2884
0.0959	0.33	3000	0.4077	787.1881
0.0691	0.43	4000	0.4019	720.3756

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1
Datasets 2.10.1
Tokenizers 0.13.2