metadata

language:
  - el
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Medium El Greco
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: el
          split: test
          args: el
        metrics:
          - name: Wer
            type: wer
            value: 10.74479940564636

Whisper Medium El Greco

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: 0.4245
Wer: 10.7448

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: 16
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: 7000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0039	2.49	1000	0.3787	12.4443
0.0017	4.98	2000	0.4010	12.2864
0.0006	7.46	3000	0.4108	11.6921
0.0004	9.95	4000	0.4221	11.5806
0.0005	12.44	5000	0.4222	11.4134
0.0006	4.03	6000	0.4230	10.9212
0.0006	9.03	7000	0.4245	10.7448

Framework versions

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