|
--- |
|
base_model: biodatlab/whisper-th-medium-combined |
|
datasets: |
|
- common_voice_17_0 |
|
library_name: transformers |
|
license: apache-2.0 |
|
metrics: |
|
- wer |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: whisper-finetune-th |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: common_voice_17_0 |
|
type: common_voice_17_0 |
|
config: th |
|
split: None |
|
args: th |
|
metrics: |
|
- type: wer |
|
value: 15.045342636924866 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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-finetune-th |
|
|
|
This model is a fine-tuned version of [biodatlab/whisper-th-medium-combined](https://huggingface.co./biodatlab/whisper-th-medium-combined) on the common_voice_17_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1015 |
|
- Wer: 15.0453 |
|
- Cer: 3.8830 |
|
|
|
## 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: 500 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:------:| |
|
| 0.2829 | 0.4873 | 1000 | 0.1345 | 20.0856 | 5.3644 | |
|
| 0.1548 | 0.9747 | 2000 | 0.1161 | 17.6348 | 4.5783 | |
|
| 0.1775 | 1.4620 | 3000 | 0.1074 | 15.9448 | 4.1193 | |
|
| 0.1477 | 1.9493 | 4000 | 0.1015 | 15.0453 | 3.8830 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
