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