metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - Ussen/swc-drc-kat
metrics:
  - wer
model-index:
  - name: whisper-medium-swc-drc-kat-1
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Ussen/swc-drc-kat
          type: Ussen/swc-drc-kat
          config: default
          split: train
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.49379203310915676

whisper-medium-swc-drc-kat-1

This model is a fine-tuned version of openai/whisper-tiny on the Ussen/swc-drc-kat dataset. It achieves the following results on the evaluation set:

Loss: 0.9701
Wer Ortho: 50.0388
Wer: 0.4938

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 500
training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.6769	2.96	1000	0.8341	51.2296	0.5072
0.365	5.93	2000	0.8083	49.3917	0.4876
0.165	8.89	3000	0.8806	51.3073	0.5067
0.059	11.85	4000	0.9701	50.0388	0.4938

Framework versions

Transformers 4.32.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.3
Tokenizers 0.13.3