---
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
  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/neuronbit-tech/finetune_only_torgo_imperative_sentences/runs/fnfnnxr1)
# no-voice-clone-large-finetune

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: 0.4678
- Wer: 18.7667

## 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0528        | 1.8692  | 100  | 0.4677          | 20.6937 |
| 0.0076        | 3.7383  | 200  | 0.4470          | 18.0848 |
| 0.0012        | 5.6075  | 300  | 0.4580          | 18.0255 |
| 0.0002        | 7.4766  | 400  | 0.4565          | 17.4326 |
| 0.0001        | 9.3458  | 500  | 0.4601          | 18.7370 |
| 0.0001        | 11.2150 | 600  | 0.4634          | 18.5295 |
| 0.0           | 13.0841 | 700  | 0.4653          | 18.5888 |
| 0.0           | 14.9533 | 800  | 0.4667          | 18.5591 |
| 0.0           | 16.8224 | 900  | 0.4675          | 18.7963 |
| 0.0           | 18.6916 | 1000 | 0.4678          | 18.7667 |


### Framework versions

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