metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-ug
results: []
datasets:
- mozilla-foundation/common_voice_15_0
pipeline_tag: automatic-speech-recognition
whisper-small-ug
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3563
- Wer: 26.8793
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 |
|---|---|---|---|---|
| 0.2677 | 1.43 | 1000 | 0.4063 | 34.1157 |
| 0.1035 | 2.85 | 2000 | 0.3375 | 29.2183 |
| 0.0226 | 4.28 | 3000 | 0.3472 | 27.5155 |
| 0.0073 | 5.71 | 4000 | 0.3563 | 26.8793 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0