---
language:
- ru
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
library_name: peft
model-index:
- name: 'Whisper Large Ru ORD 0.9 Peft PEFT 4-bit Q DoRA - Mizoru '
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mizoru/ORD/runs/jmqewt8c)
# Whisper Large Ru ORD 0.9 Peft PEFT 4-bit Q DoRA - Mizoru 

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the ORD_0.9synth dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9568
- Wer: 40.6051
- Cer: 24.1709
- Clean Wer: 30.6324
- Clean Cer: 18.3212

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     | Clean Wer | Clean Cer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:---------:|:---------:|
| 1.2498        | 1.0   | 1162 | 1.0305          | 44.9736 | 26.2819 | 34.8983   | 20.4239   |
| 1.1376        | 2.0   | 2324 | 0.9974          | 45.1705 | 26.6383 | 33.6258   | 20.2044   |
| 1.0073        | 3.0   | 3486 | 0.9692          | 41.3758 | 24.8708 | 31.3579   | 19.0546   |
| 0.9389        | 4.0   | 4648 | 0.9568          | 40.6051 | 24.1709 | 30.6324   | 18.3212   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.41.0.dev0
- Pytorch 2.3.1
- Datasets 3.2.0
- Tokenizers 0.19.1