metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper_small_Shona
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: sn_zw
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 50.85625

Whisper_small_Shona

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

Loss: 1.1174
Wer: 50.8563

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: 16
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 64
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0054	33.32	400	0.9826	51.6687
0.0009	66.64	800	1.0774	50.9062
0.0005	99.96	1200	1.1174	50.8563
0.0003	133.32	1600	1.1388	50.875
0.0003	166.64	2000	1.1461	50.925

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2