metadata

license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - Ussen/swc-drc-katanga
metrics:
  - wer
model-index:
  - name: whisper-tiny-swc-drc-kat-2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Ussen/swc-drc-katanga
          type: Ussen/swc-drc-katanga
          config: default
          split: train
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.39136057941024316

whisper-tiny-swc-drc-kat-2

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

Loss: 0.8770
Wer Ortho: 39.7101
Wer: 0.3914

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
0.3735	2.96	1000	0.6459	48.5374	0.4783
0.081	5.93	2000	0.7478	38.5969	0.3797
0.0279	8.89	3000	0.8653	38.7523	0.3813
0.0189	11.85	4000	0.8770	39.7101	0.3914

Framework versions

Transformers 4.33.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.13.1
Tokenizers 0.12.1