README.md

metadata

language:
  - it
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Medium Italian - Robust
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 it
          type: mozilla-foundation/common_voice_11_0
          config: it
          split: train
          args: it
        metrics:
          - type: wer
            value: 7.651366149266425
            name: Wer
          - type: wer
            value: 6.6
            name: WER

Whisper Medium Italian - Robust

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

• Loss: 0.1388
• WER (Augmented Test): 7.65
• WER (Real Test): 6.60

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: 5e-05
• train_batch_size: 64
• eval_batch_size: 32
• 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: 7500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.226	0.33	2500	0.2779	14.6642
0.1278	1.03	5000	0.1818	10.2049
0.0304	1.36	7500	0.1388	7.5544

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu117
• Datasets 2.7.1
• Tokenizers 0.13.2