metadata
language:
- it
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-small
model-index:
- name: Whisper Small Italian
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
args: 'config: it, split: test'
metrics:
- type: wer
value: 17.37085955328124
name: Wer
Whisper Small Italian
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2421
- Wer: 17.3709
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: 500
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4521 | 0.1 | 100 | 1.3771 | 120.3480 |
| 0.7526 | 0.21 | 200 | 0.9120 | 83.8949 |
| 0.3023 | 0.31 | 300 | 0.4427 | 26.2063 |
| 0.2718 | 0.42 | 400 | 0.4282 | 25.9013 |
| 0.2823 | 0.52 | 500 | 0.4181 | 26.2757 |
| 0.3151 | 0.63 | 600 | 0.4095 | 25.0624 |
| 0.2559 | 0.73 | 700 | 0.4028 | 25.4784 |
| 0.2727 | 0.84 | 800 | 0.2888 | 19.5491 |
| 0.2532 | 0.94 | 900 | 0.2779 | 19.3832 |
| 0.232 | 1.05 | 1000 | 0.2722 | 18.6778 |
| 0.2169 | 1.15 | 1100 | 0.2720 | 18.9268 |
| 0.2493 | 1.26 | 1200 | 0.2741 | 20.0678 |
| 0.2312 | 1.36 | 1300 | 0.2666 | 18.2767 |
| 0.2158 | 1.47 | 1400 | 0.2651 | 19.6529 |
| 0.2171 | 1.57 | 1500 | 0.2583 | 18.6087 |
| 0.2074 | 1.68 | 1600 | 0.2551 | 17.6820 |
| 0.1862 | 1.78 | 1700 | 0.2491 | 17.4124 |
| 0.2044 | 1.89 | 1800 | 0.2475 | 17.8964 |
| 0.1877 | 1.99 | 1900 | 0.2421 | 17.3709 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2