---
language:
- it
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper tiny italian - Mattia Surricchio
  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: 26.495056347012547
---

<!-- 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 tiny italian - Mattia Surricchio

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4736
- Wer: 26.4951

## 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: 32
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3889        | 0.2   | 1000 | 0.6844          | 39.1000 |
| 0.5832        | 0.4   | 2000 | 0.5691          | 31.9995 |
| 0.524         | 0.6   | 3000 | 0.4993          | 28.2672 |
| 0.4663        | 0.8   | 4000 | 0.4799          | 26.7230 |
| 0.3107        | 1.05  | 5000 | 0.4736          | 26.4951 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2