metadata
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- espnet/yodas
metrics:
- wer
model-index:
- name: Whisper Small Sr Yodas
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Yodas
type: espnet/yodas
config: sr
split: test
args: sr
metrics:
- name: Wer
type: wer
value: 0.24497708847373986
Whisper Small Sr Yodas
This model is a fine-tuned version of openai/whisper-small on the Yodas dataset. It achieves the following results on the evaluation set:
- Loss: 0.2688
- Wer Ortho: 0.3334
- Wer: 0.2450
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: 50
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.0469 | 0.24 | 500 | 0.4020 | 0.5071 | 0.4270 |
| 0.9924 | 0.49 | 1000 | 0.3401 | 0.4082 | 0.3183 |
| 0.865 | 0.73 | 1500 | 0.3047 | 0.3644 | 0.2776 |
| 0.8443 | 0.98 | 2000 | 0.2893 | 0.3623 | 0.2735 |
| 0.7377 | 1.22 | 2500 | 0.2817 | 0.3472 | 0.2591 |
| 0.6851 | 1.46 | 3000 | 0.2728 | 0.3348 | 0.2466 |
| 0.7286 | 1.71 | 3500 | 0.2702 | 0.3325 | 0.2444 |
| 0.7215 | 1.95 | 4000 | 0.2688 | 0.3334 | 0.2450 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.1