README.md

metadata

language:
  - tr
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper medium Turkish CV 3K
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 tr
          type: mozilla-foundation/common_voice_11_0
          config: tr
          split: test
          args: tr
        metrics:
          - name: Wer
            type: wer
            value: 15.901153962951717

Whisper medium Turkish CV 3K

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

• Loss: 0.3611
• Wer: 15.9012

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: 5e-05
• train_batch_size: 64
• eval_batch_size: 32
• 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: 3000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0856	3.02	1000	0.3732	20.6764
0.0119	6.03	2000	0.3684	17.5353
0.001	9.05	3000	0.3611	15.9012

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2