|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-base |
|
tags: |
|
- whisper-event |
|
- generated_from_trainer |
|
datasets: |
|
- google/fleurs |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Whisper Base Tagalog |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: google/fleurs fil_ph |
|
type: google/fleurs |
|
config: fil_ph |
|
split: test |
|
args: fil_ph |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 30.810565352304547 |
|
--- |
|
|
|
<!-- 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 Base Tagalog |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs fil_ph dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7222 |
|
- Wer: 30.8106 |
|
|
|
## 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-06 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:| |
|
| 0.5804 | 38.0 | 500 | 0.7836 | 36.0478 | |
|
| 0.1934 | 76.0 | 1000 | 0.6861 | 31.5220 | |
|
| 0.0589 | 115.0 | 1500 | 0.7040 | 32.4415 | |
|
| 0.0251 | 153.0 | 2000 | 0.7222 | 30.8106 | |
|
| 0.0154 | 192.0 | 2500 | 0.7362 | 31.3593 | |
|
| 0.0109 | 230.0 | 3000 | 0.7470 | 31.7604 | |
|
| 0.0085 | 269.0 | 3500 | 0.7562 | 31.7112 | |
|
| 0.0071 | 307.0 | 4000 | 0.7630 | 31.9874 | |
|
| 0.0064 | 346.0 | 4500 | 0.7675 | 32.0064 | |
|
| 0.0061 | 384.0 | 5000 | 0.7692 | 32.0669 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.16.2.dev0 |
|
- Tokenizers 0.15.0 |
|
|
