README.md

metadata

language:
  - it
license: apache-2.0
tags:
  - generated_from_trainer
  - whisper-event
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: luigisaetta/whisper-tiny2-it
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 it
          type: mozilla-foundation/common_voice_11_0
          config: it
          split: test
          args: it
        metrics:
          - name: Wer
            type: wer
            value: 25.91098766744631

luigisaetta/whisper-tiny2-it

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

• Loss: 0.4686
• Wer: 25.9110

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
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.5765	2.01	1000	0.5728	32.2181
0.3726	4.02	2000	0.5035	28.4606
0.2789	6.04	3000	0.4861	26.7894
0.2996	8.05	4000	0.4694	26.0279
0.2925	10.06	5000	0.4686	25.9110

Framework versions

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