---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
language:
- it
license: apache-2.0
metrics:
- wer
tags:
- whisper-event
- generated_from_trainer
model-index:
- name: Whisper Small Mixed-Italian
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_17_0 it
      type: mozilla-foundation/common_voice_17_0
      config: it
      split: test
      args: it
    metrics:
    - type: wer
      value: 10.587474512857398
      name: Wer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: it_it
      split: test
    metrics:
    - type: wer
      value: 5.77
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: facebook/multilingual_librispeech
      type: facebook/multilingual_librispeech
      config: italian
      split: test
    metrics:
    - type: wer
      value: 13.52
      name: WER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: facebook/voxpopuli
      type: facebook/voxpopuli
      config: it
      split: test
    metrics:
    - type: wer
      value: 25.87
      name: WER
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Whisper Small Mixed-Italian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_17_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1909
- Wer: 10.5875

## 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: 64
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2213        | 0.2   | 1000 | 0.2407          | 13.4605 |
| 0.1582        | 0.4   | 2000 | 0.2143          | 12.2642 |
| 0.1913        | 0.6   | 3000 | 0.2022          | 11.2328 |
| 0.1538        | 0.8   | 4000 | 0.1951          | 11.1187 |
| 0.1286        | 1.0   | 5000 | 0.1909          | 10.5875 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1