metadata

language:
  - so
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Somalia
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Somali Dataset
          type: mozilla-foundation/common_voice_11_0
          args: 'config: hi, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 0

Whisper Small Somalia

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

Loss: 0.0005
Wer: 0.0

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
0.2361	6.5359	1000	0.0235	0.6506
0.0062	13.0719	2000	0.0024	0.0
0.0007	19.6078	3000	0.0006	0.0
0.0005	26.1438	4000	0.0005	0.0

Framework versions

Transformers 4.42.3
Pytorch 2.3.0
Datasets 2.20.0
Tokenizers 0.19.1