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metadata
library_name: transformers
language:
  - it
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_4_0
metrics:
  - wer
model-index:
  - name: whisper-small-italian-tuned
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 4.0
          type: mozilla-foundation/common_voice_4_0
          config: it
          split: test
          args: 'config: it, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 20.230225666742648

whisper-small-italian-tuned

This model is a fine-tuned version of openai/whisper-small on the Common Voice 4.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2653
  • Wer: 20.2302

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: 300
  • training_steps: 4000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2668 0.5647 1000 0.3023 22.8539
0.1314 1.1293 2000 0.2735 20.6998
0.118 1.6940 3000 0.2648 20.4263
0.0644 2.2586 4000 0.2653 20.2302

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.5.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.20.3