metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-ro
results: []
whisper-medium-ro
This model is a fine-tuned version of openai/whisper-medium on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1812
- Wer: 99.5018
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 |
|---|---|---|---|---|
| 0.0777 | 1.8 | 1000 | 0.1651 | 100.1685 |
| 0.024 | 3.6 | 2000 | 0.1634 | 99.8853 |
| 0.0039 | 5.4 | 3000 | 0.1734 | 99.5484 |
| 0.001 | 7.19 | 4000 | 0.1812 | 99.5018 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.0.1
- Datasets 2.16.0
- Tokenizers 0.15.0