metadata
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-base-cs
results: []
whisper-base-cs
This model is a fine-tuned version of openai/whisper-base on the CommonVoice11 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3785
- Wer: 35.4791
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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
BASE-CS baseline performance: {'eval_loss': 2.514087438583374, 'eval_wer': 82.45662504144104, 'eval_runtime': 2620.0407, 'eval_samples_per_second': 2.944, 'eval_steps_per_second': 0.368}
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| ------ | 0.00 | 0000 | 2.5141 | 82.4566 |
| 0.2991 | 1.44 | 1000 | 0.4414 | 42.2993 |
| 0.1776 | 2.89 | 2000 | 0.3818 | 36.7573 |
| 0.0916 | 4.33 | 3000 | 0.3774 | 35.6080 |
| 0.076 | 5.78 | 4000 | 0.3785 | 35.4791 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0