README.md

metadata

language:
  - br
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Medium Breton
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 br
          type: mozilla-foundation/common_voice_11_0
          config: br
          split: test
          args: br
        metrics:
          - name: Wer
            type: wer
            value: 41.611670718999655

Whisper Medium Breton

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

• Loss: 0.8486
• Wer: 41.6117

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: 4e-06
• train_batch_size: 32
• eval_batch_size: 16
• 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
0.0602	5.03	1000	0.7324	43.6957
0.0036	10.05	2000	0.8486	41.6117
0.001	15.08	3000	0.9033	42.0458
0.0004	20.1	4000	0.9351	41.6811
0.0003	25.13	5000	0.9468	41.7853

Framework versions

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