---
base_model: openai/whisper-medium
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: 21.24248496993988
      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-medium](https://huggingface.co/openai/whisper-medium) on the b-brave/speech_disorders_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2798
- Wer: 21.2425

## 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: 50
- training_steps: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 2.4644        | 1.0417 | 50   | 6.2039          | 73.7475 |
| 3.2455        | 2.0833 | 100  | 0.3363          | 23.6473 |
| 0.1546        | 3.125  | 150  | 0.2708          | 20.8417 |
| 0.0685        | 4.1667 | 200  | 0.2790          | 19.8397 |
| 0.0427        | 5.2083 | 250  | 0.2798          | 21.2425 |


### Framework versions

- PEFT 0.12.0
- Transformers 4.43.4
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1