---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: no-voice-clone-large-finetune-test
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/testgokulepiphany/finetune_given_imperative_final/runs/p0thi8mj)
# no-voice-clone-large-finetune-test

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4622
- Wer: 20.1897

## 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: 2
- 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
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0088        | 4.6729  | 250  | 0.5014          | 21.1681 |
| 0.0079        | 9.3458  | 500  | 0.5158          | 29.2321 |
| 0.0001        | 14.0187 | 750  | 0.4311          | 23.9253 |
| 0.0           | 18.6916 | 1000 | 0.4457          | 20.5752 |
| 0.0           | 23.3645 | 1250 | 0.4520          | 20.6048 |
| 0.0           | 28.0374 | 1500 | 0.4560          | 20.1897 |
| 0.0           | 32.7103 | 1750 | 0.4588          | 20.1601 |
| 0.0           | 37.3832 | 2000 | 0.4607          | 20.1304 |
| 0.0           | 42.0561 | 2250 | 0.4618          | 20.2490 |
| 0.0           | 46.7290 | 2500 | 0.4622          | 20.1897 |


### Framework versions

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