metadata

language:
  - it
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Italian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: it, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 17.391605006569392

Whisper Small Italian

This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.1185
Wer: 17.3916

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
gradient_accumulation_steps: 1
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 954

Training results

Training Loss	Step	Validation Loss	Wer
1.4744	100	1.1852	117.6059
0.7241	200	0.7452	79.7386
0.3321	300	0.3215	21.0497
0.2930	400	0.3030	20.2129
0.2698	500	0.2982	19.7635
0.2453	600	0.2898	19.0097
0.2338	700	0.2768	18.7054
0.2402	800	0.2646	18.2214
0.2340	900	0.2581	17.3916

Framework versions

Transformers 4.25.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2