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---
language:
- it
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: luigisaetta/whisper-small3-it
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 it
type: mozilla-foundation/common_voice_11_0
config: it
split: test
args: it
metrics:
- name: Wer
type: wer
value: 10.2508
---
# Whisper Small3 Italian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2307
- Wer: 10.2508
## Model description
This model is a fine-tuning of the OpenAI Whisper Small model, on the specified dataset.
## Intended uses & limitations
This model has been developed as part of the Hugging Face Whisper Fine Tuning sprint, December 2022.
It is meant to spread the knowledge on how these models are built and can be used to develop solutions
where it is needed ASR on the Italian Language.
It has not been extensively tested. It is possible that on other datasets the accuracy will be lower.
Please, test it before using it.
## Training and evaluation data
Trained and tested on Mozilla Common Voice, vers. 11
## Training procedure
The script **run.sh**, and the Python file, used for the training are saved in the repository.
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 8e-06
- train_batch_size: 64
- eval_batch_size: 32
- 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: 6000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.226 | 2.01 | 1000 | 0.2494 | 11.3684 |
| 0.1017 | 4.02 | 2000 | 0.2403 | 10.6029 |
| 0.0491 | 6.03 | 3000 | 0.2549 | 10.9591 |
| 0.1102 | 8.04 | 4000 | 0.2307 | 10.2508 |
| 0.0384 | 10.05 | 5000 | 0.2592 | 10.5903 |
| 0.0285 | 12.06 | 6000 | 0.2537 | 10.5026 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|