metadata
language:
- hre
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- ntviet/hre-audio-dataset3
metrics:
- wer
model-index:
- name: Whisper Small Hre 3.2 - 500 steps, streaming mode - NT Viet
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Hre audio dataset 3
type: ntviet/hre-audio-dataset3
config: default
split: test
args: default
metrics:
- name: Wer
type: wer
value: 59.10273081924578
Whisper Small Hre 3.2 - 500 steps, streaming mode - NT Viet
This model is a fine-tuned version of openai/whisper-small on the Hre audio dataset 3 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2957
- Wer Ortho: 60.7702
- Wer: 59.1027
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.1271 | 5.06 | 500 | 1.2957 | 60.7702 | 59.1027 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2