---
language:
- it
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Italian
  results: []
---

<!-- 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 Italian

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the type: common_voice_11_0, name: Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2447
- Wer: 56.4799

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8509        | 0.13  | 100  | 0.8546          | 164.0451 |
| 0.4916        | 0.26  | 200  | 0.5683          | 119.5052 |
| 0.2073        | 0.39  | 300  | 0.2744          | 41.9652  |
| 0.1948        | 0.52  | 400  | 0.2681          | 62.8181  |
| 0.182         | 0.65  | 500  | 0.2678          | 51.2139  |
| 0.1658        | 0.78  | 600  | 0.2526          | 59.0466  |
| 0.1684        | 0.91  | 700  | 0.2447          | 56.4799  |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0