---
library_name: transformers
language:
- dv
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_15_0
metrics:
- wer
model-index:
- name: Whisper Base Dv - Nuwan
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 15
      type: fsicoli/common_voice_15_0
      config: dv
      split: test
      args: dv
    metrics:
    - name: Wer
      type: wer
      value: 110.55416318574214
---

<!-- 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 Base Dv - Nuwan

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 15 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9098
- Wer Ortho: 194.4305
- Wer: 110.5542

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer      |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:--------:|
| 2.3429        | 2.3669  | 400  | 2.2946          | 202.8266  | 113.8993 |
| 1.2184        | 4.7337  | 800  | 1.2136          | 203.0430  | 112.1693 |
| 1.0668        | 7.1006  | 1200 | 1.0778          | 201.4657  | 111.3182 |
| 1.0197        | 9.4675  | 1600 | 1.0351          | 199.5743  | 111.5619 |
| 0.9854        | 11.8343 | 2000 | 1.0064          | 194.9470  | 110.4323 |
| 0.9512        | 14.2012 | 2400 | 0.9839          | 189.6776  | 109.2157 |
| 0.9335        | 16.5680 | 2800 | 0.9635          | 189.0215  | 109.1896 |
| 0.9074        | 18.9349 | 3200 | 0.9436          | 188.9866  | 109.4072 |
| 0.8867        | 21.3018 | 3600 | 0.9265          | 193.4394  | 110.2983 |
| 0.8529        | 23.6686 | 4000 | 0.9098          | 194.4305  | 110.5542 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.22.1