|
--- |
|
language: |
|
- uz |
|
license: mit |
|
base_model: openai/whisper-large-v3-turbo |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- mozilla-foundation/common_voice_16_1 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Large v3 Turbo - Bahriddin Muminov |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice 16.1 |
|
type: mozilla-foundation/common_voice_16_1 |
|
config: uz |
|
split: test |
|
args: 'config: uz, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 25.073985739794963 |
|
--- |
|
|
|
<!-- 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 Large v3 Turbo - Bahriddin Muminov |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 16.1 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2643 |
|
- Wer: 25.0740 |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- training_steps: 10000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
|
| 0.3109 | 0.04 | 2000 | 0.4220 | 36.8942 | |
|
| 0.2529 | 0.07 | 4000 | 0.3593 | 31.0915 | |
|
| 0.2123 | 0.11 | 6000 | 0.3150 | 28.2694 | |
|
| 0.1936 | 0.14 | 8000 | 0.2773 | 27.4353 | |
|
| 0.1716 | 0.18 | 10000 | 0.2643 | 25.0740 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
