README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: kab
          split: test
          args: kab
        metrics:
          - name: Wer
            type: wer
            value: 41.57367739364352

openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5889
• Wer: 41.5737

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: 64
• eval_batch_size: 32
• seed: 42
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 400
• training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.4105	1.42	1000	0.5508	48.1244
0.258	2.84	2000	0.4905	42.0295
0.0998	4.27	3000	0.5220	41.6808
0.064	5.69	4000	0.5547	41.4753
0.0356	7.11	5000	0.5889	41.5737

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2