metadata

language:
  - dv
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Small Dv - Peter Gelderbloem
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 13
          type: mozilla-foundation/common_voice_13_0
          config: div
          split: None
        metrics:
          - name: Wer
            type: wer
            value: 11.249434920193343

Whisper Small Dv - Peter Gelderbloem

This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:

Loss: 0.2863
Wer Ortho: 57.7129
Wer: 11.2494

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Wer Ortho
0.1248	1.63	500	0.1684	12.9881	62.0447
0.0484	3.26	1000	0.1629	11.6493	58.6113
0.0315	4.89	1500	0.1878	11.7224	58.9386
0.0125	6.51	2000	0.2308	11.0895	57.2185
0.0058	8.14	2500	0.2671	11.0773	57.6224
0.0049	9.77	3000	0.2843	11.2564	57.6572
0.0033	11.4	3500	0.2845	11.0982	57.1558
0.0046	13.03	4000	0.2863	57.7129	11.2494

Framework versions

Transformers 4.31.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.12.1