|
--- |
|
language: |
|
- vi |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v3 |
|
tags: |
|
- hf-asr-leaderboard |
|
- generated_from_trainer |
|
datasets: |
|
- google/fleurs |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Large V3 Vi - Prateek Jain |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: google/fleurs |
|
type: google/fleurs |
|
config: vi_vn |
|
split: None |
|
args: 'config: vi, split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 218.83302440531355 |
|
--- |
|
|
|
<!-- 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 Vi - Prateek Jain |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the google/fleurs dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2355 |
|
- Wer: 218.8330 |
|
|
|
## 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: 250 |
|
- training_steps: 1500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.0148 | 2.66 | 500 | 0.2193 | 80.1012 | |
|
| 0.0014 | 5.32 | 1000 | 0.2275 | 247.5556 | |
|
| 0.0004 | 7.98 | 1500 | 0.2355 | 218.8330 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.1 |
|
|
