|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: openai/whisper-large-v3 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: 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/testgokulepiphany/finetune_voice_clone_imperative_final/runs/w4xycre7) |
|
|
# 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: 0.4491 |
|
|
- Wer: 16.9582 |
|
|
|
|
|
## 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: 5000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:-------:|:----:|:---------------:|:-------:| |
|
|
| 0.1608 | 0.8460 | 250 | 0.5171 | 25.8227 | |
|
|
| 0.0607 | 1.6920 | 500 | 0.4735 | 28.3427 | |
|
|
| 0.0255 | 2.5381 | 750 | 0.4274 | 25.4966 | |
|
|
| 0.0138 | 3.3841 | 1000 | 0.4327 | 18.9742 | |
|
|
| 0.0013 | 4.2301 | 1250 | 0.4508 | 20.8123 | |
|
|
| 0.0129 | 5.0761 | 1500 | 0.4107 | 21.2274 | |
|
|
| 0.0005 | 5.9222 | 1750 | 0.4218 | 21.5535 | |
|
|
| 0.0018 | 6.7682 | 2000 | 0.4256 | 17.5215 | |
|
|
| 0.0021 | 7.6142 | 2250 | 0.4224 | 18.1441 | |
|
|
| 0.0015 | 8.4602 | 2500 | 0.4298 | 18.0255 | |
|
|
| 0.0008 | 9.3063 | 2750 | 0.4376 | 18.1441 | |
|
|
| 0.0005 | 10.1523 | 3000 | 0.4418 | 17.6697 | |
|
|
| 0.0014 | 10.9983 | 3250 | 0.4442 | 17.5808 | |
|
|
| 0.0002 | 11.8443 | 3500 | 0.4422 | 17.1064 | |
|
|
| 0.0009 | 12.6904 | 3750 | 0.4408 | 17.1657 | |
|
|
| 0.0002 | 13.5364 | 4000 | 0.4438 | 16.9878 | |
|
|
| 0.0009 | 14.3824 | 4250 | 0.4452 | 16.7803 | |
|
|
| 0.0007 | 15.2284 | 4500 | 0.4457 | 16.8989 | |
|
|
| 0.0 | 16.0745 | 4750 | 0.4485 | 16.8693 | |
|
|
| 0.0 | 16.9205 | 5000 | 0.4491 | 16.9582 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.45.2 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.20.3 |
|
|
|
