---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper largeV2 Italian MLS
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: facebook/multilingual_librispeech italian
      type: facebook/multilingual_librispeech
      config: italian
      split: test
      args: italian
    metrics:
    - name: Wer
      type: wer
      value: 8.335297167365791
---

<!-- 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 largeV2 Italian MLS

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the facebook/multilingual_librispeech italian dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2051
- Wer: 8.3353

## Model description


The model is fine-tuned for 4000 updates/steps on multilingual librispeech Italian train data.

- Zero-shot                        - 13.8 (MLS Italian test)
- Fine-tune MLS Italian train      - 8.33 (MLS Italian test) (-40%)

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1115        | 1.02  | 1000 | 0.2116          | 9.4217 |
| 0.0867        | 2.03  | 2000 | 0.1964          | 9.7823 |
| 0.0447        | 3.05  | 3000 | 0.2001          | 9.6409 |
| 0.0426        | 4.07  | 4000 | 0.2051          | 8.3353 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2