metadata

base_model: openai/whisper-large-v3
datasets:
  - mozilla-foundation/common_voice_11_0
language:
  - pl
license: apache-2.0
metrics:
  - wer
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
model-index:
  - name: Whisper Large V3 pl - Chee Li
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: pl
          split: None
          args: 'config: pl split: test'
        metrics:
          - type: wer
            value: 614.9727204417002
            name: Wer

Whisper Large V3 pl - Chee Li

This model is a fine-tuned version of openai/whisper-large-v3 on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1865
Wer: 614.9727

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1328	0.6439	1000	0.2206	275.0400
0.0517	1.2878	2000	0.2183	668.6775
0.0501	1.9317	3000	0.1740	468.4439
0.022	2.5757	4000	0.1865	614.9727

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1