---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: UDA-LIDI-Whisper-large-v3-turbo-ECU-911
  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. -->

# UDA-LIDI-Whisper-large-v3-turbo-ECU-911

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8685
- Wer: 40.1779

## 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: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.7289        | 1.0    | 91   | 0.6513          | 40.7708 |
| 0.4426        | 2.0    | 182  | 0.6487          | 40.1779 |
| 0.298         | 3.0    | 273  | 0.6699          | 40.1186 |
| 0.2058        | 4.0    | 364  | 0.6912          | 42.6285 |
| 0.1435        | 5.0    | 455  | 0.7103          | 39.6838 |
| 0.1022        | 6.0    | 546  | 0.7852          | 41.8379 |
| 0.0735        | 7.0    | 637  | 0.8315          | 40.6324 |
| 0.0568        | 8.0    | 728  | 0.8265          | 40.6126 |
| 0.0444        | 9.0    | 819  | 0.8538          | 40.0198 |
| 0.0399        | 9.8950 | 900  | 0.8685          | 40.1779 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0