---
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 Medium
  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: 100.0
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Medium

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: 0.1865
- Wer: 100.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 48
- training_steps: 256
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.423         | 0.375 | 48   | 0.3535          | 106.0166 |
| 0.3121        | 0.75  | 96   | 0.2261          | 100.0    |
| 0.2534        | 1.125 | 144  | 0.1995          | 100.0    |
| 0.147         | 1.5   | 192  | 0.1973          | 99.7925  |
| 0.1161        | 1.875 | 240  | 0.1865          | 100.0    |


### Framework versions

- PEFT 0.11.2.dev0
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1