---
base_model: openai/whisper-large-v3
datasets:
- b-brave/speech_disorders_voice
language:
- it
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Large v3
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: b-brave/speech_disorders_voice
      type: b-brave/speech_disorders_voice
      config: default
      split: train
      args: default
    metrics:
    - type: wer
      value: 23.517382413087933
      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 Large v3

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the b-brave/speech_disorders_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3055
- Wer: 23.5174

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 16
- 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: 128
- training_steps: 256
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.3683        | 0.9481 | 64   | 0.3394          | 19.8364 |
| 0.1165        | 1.8963 | 128  | 0.3326          | 15.3374 |
| 0.0332        | 2.8444 | 192  | 0.3112          | 19.6319 |
| 0.013         | 3.7926 | 256  | 0.3055          | 23.5174 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.2.0
- Datasets 2.21.0
- Tokenizers 0.19.1