metadata

license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
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: common_voice_11_0
          type: common_voice_11_0
          config: ga-IE
          split: test
          args: ga-IE
        metrics:
          - name: Wer
            type: wer
            value: 35.22067363530778

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: 1.1422
Wer: 35.2207

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: 16
eval_batch_size: 8
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
0.1137	4.02	1000	0.9072	40.0987
0.0153	9.02	2000	1.0351	38.7631
0.0042	14.01	3000	1.0507	36.4402
0.0013	19.0	4000	1.0924	36.2660
0.0003	23.02	5000	1.1422	35.2207
0.0001	28.02	6000	1.1688	35.3368
0.0001	33.01	7000	1.1768	35.5110

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.9.1.dev0
Tokenizers 0.13.2