metadata

library_name: transformers
language:
  - ru
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Tiny finetuned RU
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: ru
          split: None
          args: 'config: ru, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 41.04365802952346

Whisper Tiny finetuned RU

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5156
Wer: 41.0437

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 250
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.511	0.2187	2000	0.5548	43.4606
0.4345	0.4374	4000	0.5156	41.0437

Framework versions

Transformers 4.45.2
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0