metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small 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: 20.66525391659729
Whisper Small Tagalog
This model is a fine-tuned version of openai/whisper-small on the google/fleurs fil_ph dataset. It achieves the following results on the evaluation set:
- Loss: 0.6250
- Wer: 20.6653
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: 5e-07
- 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: 10000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0759 | 76.0 | 1000 | 0.5043 | 22.2622 |
0.0099 | 153.0 | 2000 | 0.5464 | 21.3653 |
0.0043 | 230.0 | 3000 | 0.5707 | 21.2215 |
0.0024 | 307.0 | 4000 | 0.5909 | 20.9377 |
0.0015 | 384.0 | 5000 | 0.6090 | 20.6728 |
0.001 | 461.0 | 6000 | 0.6250 | 20.6653 |
0.0007 | 538.0 | 7000 | 0.6395 | 20.8582 |
0.0005 | 615.0 | 8000 | 0.6519 | 20.9415 |
0.0004 | 692.0 | 9000 | 0.6613 | 20.9112 |
0.0004 | 769.0 | 10000 | 0.6653 | 20.9377 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0