|
--- |
|
language: |
|
- ta |
|
license: apache-2.0 |
|
base_model: openai/whisper-medium |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- tamilcustomvoice |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper tiny custom |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: custom dataset |
|
type: tamilcustomvoice |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 7.28476821192053 |
|
--- |
|
|
|
<!-- 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 tiny custom |
|
|
|
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the custom dataset dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0315 |
|
- Wer Ortho: 9.2105 |
|
- Wer: 7.2848 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: constant_with_warmup |
|
- lr_scheduler_warmup_steps: 50 |
|
- training_steps: 500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| |
|
| 1.6536 | 2.5 | 50 | 0.4681 | 57.8947 | 50.9934 | |
|
| 0.0732 | 5.0 | 100 | 0.0820 | 19.7368 | 15.2318 | |
|
| 0.0076 | 7.5 | 150 | 0.0396 | 9.2105 | 7.9470 | |
|
| 0.0013 | 10.0 | 200 | 0.0336 | 9.2105 | 8.6093 | |
|
| 0.0007 | 12.5 | 250 | 0.0356 | 7.8947 | 5.9603 | |
|
| 0.0005 | 15.0 | 300 | 0.0339 | 7.8947 | 5.9603 | |
|
| 0.0004 | 17.5 | 350 | 0.0326 | 7.8947 | 5.9603 | |
|
| 0.0003 | 20.0 | 400 | 0.0323 | 7.8947 | 5.9603 | |
|
| 0.0003 | 22.5 | 450 | 0.0320 | 9.2105 | 7.2848 | |
|
| 0.0002 | 25.0 | 500 | 0.0315 | 9.2105 | 7.2848 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
