README.md

metadata

language:
  - sl
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-medium
model-index:
  - name: Whisper Medium Slovenian CV11
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 sl
          type: mozilla-foundation/common_voice_11_0
          config: sl
          split: test
          args: sl
        metrics:
          - type: wer
            value: 17.93002915451895
            name: Wer

Whisper Medium Slovenian CV11

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

• Loss: 0.4331
• Wer: 17.9300

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: 64
• eval_batch_size: 32
• 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: 500
• training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.003	26.32	1000	0.3665	19.0379
0.0001	52.63	2000	0.4114	18.1778
0.0001	78.95	3000	0.4331	17.9300
0.0	105.26	4000	0.4458	18.0321
0.0	131.58	5000	0.4512	17.9883

Framework versions

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