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---
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 Tiny It 2 - Gianluca Ruberto
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: it
split: test[:10%]
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 43.392956184137546
---
# Whisper Tiny It 2 - Gianluca Ruberto
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.711485
- Wer: 43.392956
## Model description
This model is the openai whisper small transformer adapted for Italian audio to text transcription. This model has weight decay set to 0.3 to cope with overfitting.
## Intended uses & limitations
The model is available through its [HuggingFace web app](https://huggingface.co/spaces/GIanlucaRub/whisper-it)
## Training and evaluation data
Data used for training is the initial 10% of train and validation of [Italian Common Voice](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/it/train) 11.0 from Mozilla Foundation.
The dataset used for evaluation is the initial 10% of test of Italian Common Voice.
Unfortunately weight decay showed to have slightly worse result also on the evaluation dataset.
## Training procedure
After loading the pre trained model, it has been trained on the dataset.
### 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
- training_steps: 4000
- mixed_precision_training: Native AMP
- weight_decay: 0.3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5837 | 0.95 | 1000 | 0.790046 | 50.6032 |
| 0.4186 | 1.91 | 2000 | 0.730115 | 46.0067 |
| 0.3154 | 2.86 | 3000 | 0.712776 | 44.114 |
| 0.2676 | 3.82 | 4000 | 0.711485 | 43.393 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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