metadata
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: windanam-whisper-medium
results: []
windanam-whisper-medium
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: 0.1407
- Wer: 0.2006
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
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5665 | 0.16 | 1000 | 0.3283 | 0.3337 |
| 0.3998 | 0.31 | 2000 | 0.2489 | 0.2825 |
| 0.35 | 0.47 | 3000 | 0.2061 | 0.2549 |
| 0.3084 | 0.62 | 4000 | 0.1842 | 0.2263 |
| 0.2603 | 0.78 | 5000 | 0.1693 | 0.2169 |
| 0.2414 | 0.93 | 6000 | 0.1592 | 0.2097 |
| 0.1604 | 1.09 | 7000 | 0.1519 | 0.2009 |
| 0.1584 | 1.24 | 8000 | 0.1474 | 0.2007 |
| 0.1442 | 1.4 | 9000 | 0.1427 | 0.1980 |
| 0.1391 | 1.55 | 10000 | 0.1407 | 0.2006 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1