metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-squeezeformer-NSQU-whisper
results: []
Whisper-squeezeformer-NSQU-whisper
This model is a fine-tuned version of openai/whisper-small on the LibriSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.1511
- Wer: 6.8035
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: 20
- 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: 2500
- training_steps: 30000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.8718 | 1.0 | 2500 | 3.8609 | 111.8590 |
| 2.5628 | 2.0 | 5000 | 0.2978 | 15.6193 |
| 0.1698 | 3.0 | 7500 | 0.2218 | 11.0906 |
| 0.0867 | 4.0 | 10000 | 0.2011 | 10.1891 |
| 0.1697 | 5.0 | 12500 | 0.1641 | 8.9851 |
| 0.0993 | 6.0 | 15000 | 0.1553 | 7.8039 |
| 0.0651 | 7.0 | 17500 | 0.1555 | 7.2448 |
| 0.0468 | 8.0 | 20000 | 0.1569 | 7.1497 |
| 0.2168 | 9.0 | 22500 | 0.1509 | 7.0507 |
| 0.1467 | 10.0 | 25000 | 0.1494 | 6.9671 |
| 0.1113 | 11.0 | 27500 | 0.1493 | 6.7597 |
| 0.0914 | 12.0 | 30000 | 0.1511 | 6.8035 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0