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---
library_name: peft
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- base_model:adapter:openai/whisper-small
- lora
- transformers
datasets:
- VladS159/romanian_speech_dataset_with_5_percent_synthetic_data
metrics:
- wer
model-index:
- name: Whisper Small Ro - PEFT
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Romanian Speech Dataset + 5% Synthetic
      type: VladS159/romanian_speech_dataset_with_5_percent_synthetic_data
    metrics:
    - type: wer
      value: 106.59810174871058
      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 Small Ro - PEFT

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Romanian Speech Dataset + 5% Synthetic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4248
- Wer: 106.5981

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer      |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.0921        | 0.0113 | 50   | 1.0811          | 95.9014  |
| 0.6328        | 0.0227 | 100  | 0.4248          | 106.5981 |


### Framework versions

- PEFT 0.18.1.dev0
- Transformers 4.57.1
- Pytorch 2.9.1+rocm6.4
- Datasets 3.6.0
- Tokenizers 0.22.1