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

<!-- 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. -->

[<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/fdm77w56)
[<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/1aifdj7m)
# Whisper Small Ru ORD 0.9 Peft PEFT 4-bit Q DoRA - Mizoru 

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the ORD_0.9 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1643
- Wer: 58.1771
- Cer: 31.9056
- Clean Wer: 50.6879
- Clean Cer: 26.1504

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:---------:|:---------:|
| 1.1675        | 1.0   | 550  | 1.2152          | 60.5918 | 33.7819 | 55.0018   | 28.7141   |
| 1.1217        | 2.0   | 1100 | 1.1698          | 62.6194 | 35.1450 | 54.1401   | 29.5194   |
| 0.9579        | 3.0   | 1650 | 1.1557          | 58.2105 | 32.0513 | 51.0548   | 26.5161   |
| 0.7957        | 4.0   | 2200 | 1.1643          | 58.1771 | 31.9056 | 50.6879   | 26.1504   |


### Framework versions

- PEFT 0.11.1.dev0
- Transformers 4.41.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1