---
library_name: transformers
language:
- dv
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: "Whisper \uFF2Dedium Dv - Leon Lee"
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: dv
      split: test
      args: dv
    metrics:
    - name: Wer
      type: wer
      value: 8.432729422401502
---

<!-- 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 Ｍedium Dv - Leon Lee

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2803
- Wer Ortho: 48.8335
- Wer: 8.4327

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.1344        | 0.8157  | 500  | 0.1613          | 59.9206   | 12.1049 |
| 0.0732        | 1.6313  | 1000 | 0.1382          | 52.9285   | 10.2271 |
| 0.0411        | 2.4470  | 1500 | 0.1447          | 52.3087   | 9.7628  |
| 0.0244        | 3.2626  | 2000 | 0.1538          | 51.6749   | 9.4534  |
| 0.0164        | 4.0783  | 2500 | 0.1839          | 53.8617   | 9.4290  |
| 0.0162        | 4.8940  | 3000 | 0.1734          | 51.7863   | 9.0604  |
| 0.0086        | 5.7096  | 3500 | 0.1962          | 50.8949   | 9.0222  |
| 0.0048        | 6.5253  | 4000 | 0.2299          | 50.7904   | 8.8205  |
| 0.003         | 7.3409  | 4500 | 0.2336          | 50.7487   | 8.8344  |
| 0.0017        | 8.1566  | 5000 | 0.2303          | 50.2472   | 8.6275  |
| 0.0017        | 8.9723  | 5500 | 0.2455          | 49.9896   | 8.6327  |
| 0.0005        | 9.7879  | 6000 | 0.2551          | 49.8015   | 8.5371  |
| 0.0001        | 10.6036 | 6500 | 0.2682          | 48.8962   | 8.4414  |
| 0.0           | 11.4192 | 7000 | 0.2732          | 48.6663   | 8.4206  |
| 0.0           | 12.2349 | 7500 | 0.2800          | 48.8892   | 8.4605  |
| 0.0           | 13.0506 | 8000 | 0.2803          | 48.8335   | 8.4327  |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0