metadata

license: apache-2.0
tags:
  - generated_from_trainer
  - hf-asr-leaderboard
  - whisper-event
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-medium
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: el, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 11.469167904903417

openai/whisper-medium

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

Loss: 0.3367
Wer: 11.4692

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: 32
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: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0108	4.04	1000	0.2423	12.7600
0.0013	9.04	2000	0.2810	11.9799
0.0001	14.04	3000	0.3152	11.5435
0.0001	19.04	4000	0.3304	11.4320
0.0001	24.04	5000	0.3367	11.4692

Framework versions

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