---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-nope-en
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_16_1
      type: common_voice_16_1
      config: en
      split: test
      args: en
    metrics:
    - type: wer
      value: 109.32982917214191
      name: Wer
---

<!-- 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-large-v3-turbo-nope-en

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6282
- Wer: 109.3298
- Cer: 76.3723

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer       | Cer      |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:--------:|
| No log        | 0     | 0    | 8.8537          | 1137.9325 | 452.8176 |
| 4.2788        | 0.1   | 500  | 4.0872          | 160.9724  | 102.4893 |
| 4.1267        | 0.2   | 1000 | 3.8964          | 106.7017  | 73.6642  |
| 4.0032        | 0.3   | 1500 | 3.8182          | 110.0745  | 73.1695  |
| 3.8969        | 0.4   | 2000 | 3.8130          | 108.3224  | 77.8156  |
| 3.8894        | 0.5   | 2500 | 3.6948          | 109.8117  | 75.5939  |
| 3.9464        | 0.6   | 3000 | 3.6782          | 111.5637  | 76.2183  |
| 3.8295        | 0.7   | 3500 | 3.6481          | 133.2457  | 100.4784 |
| 3.75          | 0.8   | 4000 | 3.6358          | 112.1770  | 78.8859  |
| 3.7714        | 0.9   | 4500 | 3.6292          | 110.1183  | 77.8480  |
| 3.8284        | 1.0   | 5000 | 3.6282          | 109.3298  | 76.3723  |


### Framework versions

- Transformers 4.54.1
- Pytorch 2.8.0.dev20250319+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4