---
library_name: transformers
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper_large_v3_turbo_v2
  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. -->

# Whisper_large_v3_turbo_v2

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: 0.6363
- Wer: 31.7384

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.8106        | 1.1834  | 500  | 1.0268          | 93.4686 |
| 0.5518        | 2.3669  | 1000 | 0.8523          | 56.8544 |
| 0.4203        | 3.5503  | 1500 | 0.7787          | 52.2696 |
| 0.2934        | 4.7337  | 2000 | 0.7357          | 48.8402 |
| 0.2243        | 5.9172  | 2500 | 0.7544          | 49.3678 |
| 0.1262        | 7.1006  | 3000 | 0.7770          | 49.9682 |
| 0.1038        | 8.2840  | 3500 | 0.7445          | 43.7824 |
| 0.0791        | 9.4675  | 4000 | 0.7615          | 44.6193 |
| 0.057         | 10.6509 | 4500 | 0.7432          | 41.0079 |
| 0.0441        | 11.8343 | 5000 | 0.7307          | 40.3166 |
| 0.0313        | 13.0178 | 5500 | 0.7222          | 38.7519 |
| 0.0147        | 14.2012 | 6000 | 0.7173          | 37.2965 |
| 0.0091        | 15.3846 | 6500 | 0.6866          | 34.8949 |
| 0.0022        | 16.5680 | 7000 | 0.6540          | 33.5031 |
| 0.0025        | 17.7515 | 7500 | 0.6488          | 32.5298 |
| 0.0004        | 18.9349 | 8000 | 0.6363          | 31.7384 |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3