---
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small Dv - BanUrsus
  results: []
datasets:
- mozilla-foundation/common_voice_13_0
---

<!-- 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 Dv - BanUrsus

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2999
- Wer Ortho: 56.6961
- Wer: 10.8095

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.1219        | 1.63  | 500  | 0.1725          | 63.1729   | 13.4698 |
| 0.0472        | 3.26  | 1000 | 0.1644          | 58.0820   | 11.8076 |
| 0.0288        | 4.89  | 1500 | 0.1815          | 58.2283   | 11.3294 |
| 0.0067        | 6.53  | 2000 | 0.2322          | 59.0919   | 11.2946 |
| 0.0018        | 8.16  | 2500 | 0.2608          | 57.5179   | 11.0217 |
| 0.001         | 9.79  | 3000 | 0.2815          | 57.1558   | 10.8895 |
| 0.0002        | 11.42 | 3500 | 0.2943          | 56.8633   | 10.8634 |
| 0.0002        | 13.05 | 4000 | 0.2999          | 56.6961   | 10.8095 |


### Framework versions

- Transformers 4.39.2
- Pytorch 1.13.0+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1