metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - google/fleurs
metrics:
  - wer
model-index:
  - name: Whisper_small_Somali
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: google/fleurs so_so
          type: google/fleurs
          config: so_so
          split: test
        metrics:
          - name: Wer
            type: wer
            value: 66.59499689890428

Whisper_small_Somali

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

Loss: 2.0764
Wer: 66.5950

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
0.0205	30.74	400	1.8418	67.2524
0.0012	61.52	800	2.0764	66.5950
0.0006	92.3	1200	2.1537	67.6452
0.0004	123.07	1600	2.1930	67.1367
0.0004	153.81	2000	2.2065	66.9299

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu117
Datasets 2.7.1
Tokenizers 0.13.2