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---
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
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