---
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: 37.106017191977074
      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: 0.4423
- Wer: 37.1060
- Cer: 27.9222
- Lr: 0.0000

## 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: 0.0003
- 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: 0.3
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer      | Cer      | Lr     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:--------:|:------:|
| 3.8497        | 1.0     | 168  | 2.1950          | 120.4871 | 80.3257  | 0.0001 |
| 1.0999        | 2.0     | 336  | 0.8517          | 88.6819  | 73.6538  | 0.0001 |
| 0.7773        | 3.0     | 504  | 0.7060          | 224.9284 | 212.4245 | 0.0002 |
| 0.5742        | 4.0     | 672  | 0.5562          | 50.1433  | 34.0163  | 0.0002 |
| 0.3652        | 5.0     | 840  | 0.5426          | 103.2951 | 88.8101  | 0.0003 |
| 0.2244        | 6.0     | 1008 | 0.5211          | 100.2865 | 66.5353  | 0.0003 |
| 0.1522        | 7.0     | 1176 | 0.4991          | 48.9971  | 35.5398  | 0.0002 |
| 0.0863        | 8.0     | 1344 | 0.4682          | 39.1117  | 28.3951  | 0.0002 |
| 0.0472        | 9.0     | 1512 | 0.4743          | 44.1261  | 30.9693  | 0.0002 |
| 0.021         | 10.0    | 1680 | 0.4590          | 40.5444  | 29.1305  | 0.0002 |
| 0.0106        | 11.0    | 1848 | 0.4460          | 37.3926  | 27.1868  | 0.0001 |
| 0.0053        | 12.0    | 2016 | 0.4420          | 36.6762  | 27.4494  | 0.0001 |
| 0.0034        | 13.0    | 2184 | 0.4395          | 37.9656  | 28.4476  | 0.0001 |
| 0.0021        | 14.0    | 2352 | 0.4398          | 36.8195  | 27.6596  | 0.0001 |
| 0.0023        | 15.0    | 2520 | 0.4422          | 37.1060  | 27.9222  | 0.0000 |
| 0.0021        | 15.9075 | 2672 | 0.4423          | 37.1060  | 27.9222  | 0.0000 |


### Framework versions

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