---
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](https://huggingface.co/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
<!-- - seed: 42 -->
- 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
<!-- - mixed_precision_training: Native AMP -->

### 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