---
library_name: peft
language:
- it
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- b-brave-clean
metrics:
- wer
model-index:
- name: Whisper Medium
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: b-brave-clean
      type: b-brave-clean
      config: default
      split: test
      args: default
    metrics:
    - type: wer
      value: 69.19770773638967
      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 Medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the b-brave-clean dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8245
- Wer: 69.1977
- Cer: 45.5477

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.4
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      | Cer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 4.2121        | 1.0   | 251  | 4.2340          | 150.7163 | 87.2603  |
| 1.0726        | 2.0   | 502  | 1.1107          | 79.9427  | 52.9288  |
| 0.8421        | 3.0   | 753  | 0.9359          | 203.4384 | 152.2721 |
| 0.6134        | 4.0   | 1004 | 0.8391          | 102.2923 | 77.7515  |
| 0.4891        | 5.0   | 1255 | 0.8245          | 69.1977  | 45.5477  |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.2.0
- Datasets 3.2.0
- Tokenizers 0.21.0