metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./3382
results: []
./3382
This model is a fine-tuned version of openai/whisper-medium.en on the 3382 NYC 1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6304
- Wer Ortho: 32.2501
- Wer: 23.5222
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: 3e-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.5524 | 0.5256 | 100 | 1.0430 | 42.1375 | 33.6570 |
| 1.0535 | 1.0512 | 200 | 0.8779 | 37.1493 | 27.9815 |
| 0.8222 | 1.5769 | 300 | 0.7495 | 35.4208 | 26.5674 |
| 0.6909 | 2.1025 | 400 | 0.6826 | 33.2082 | 24.5121 |
| 0.5843 | 2.6281 | 500 | 0.6558 | 32.8625 | 24.1350 |
| 0.5347 | 3.1537 | 600 | 0.6436 | 32.4773 | 23.5693 |
| 0.4819 | 3.6794 | 700 | 0.6377 | 33.5243 | 24.4555 |
| 0.4922 | 4.2050 | 800 | 0.6338 | 31.9933 | 23.0980 |
| 0.4638 | 4.7306 | 900 | 0.6318 | 32.1513 | 23.4845 |
| 0.4362 | 5.2562 | 1000 | 0.6304 | 32.2501 | 23.5222 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1