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