metadata
library_name: transformers
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large V2
results: []
Whisper Large V2
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5449
- Wer: 25.0953
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-05
- train_batch_size: 12
- 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: 20
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.841 | 0.2239 | 15 | 0.5933 | 48.4347 |
| 0.5965 | 0.4478 | 30 | 0.5012 | 27.9249 |
| 0.5018 | 0.6716 | 45 | 0.4670 | 25.0251 |
| 0.4578 | 0.8955 | 60 | 0.4569 | 27.6390 |
| 0.3824 | 1.1194 | 75 | 0.4603 | 27.2978 |
| 0.2738 | 1.3433 | 90 | 0.4537 | 25.0301 |
| 0.2375 | 1.5672 | 105 | 0.4516 | 24.4632 |
| 0.2573 | 1.7910 | 120 | 0.4381 | 25.3512 |
| 0.241 | 2.0149 | 135 | 0.4379 | 25.4766 |
| 0.1265 | 2.2388 | 150 | 0.4624 | 23.7809 |
| 0.1391 | 2.4627 | 165 | 0.4588 | 26.6406 |
| 0.1242 | 2.6866 | 180 | 0.4572 | 24.7642 |
| 0.1227 | 2.9104 | 195 | 0.4561 | 27.5738 |
| 0.0774 | 3.1343 | 210 | 0.4790 | 24.2474 |
| 0.0543 | 3.3582 | 225 | 0.4931 | 31.8483 |
| 0.0506 | 3.5821 | 240 | 0.5087 | 25.3010 |
| 0.056 | 3.8060 | 255 | 0.4933 | 27.6942 |
| 0.0527 | 4.0299 | 270 | 0.5009 | 26.2543 |
| 0.0233 | 4.2537 | 285 | 0.5447 | 27.8999 |
| 0.0193 | 4.4776 | 300 | 0.5458 | 27.0570 |
| 0.0167 | 4.7015 | 315 | 0.5421 | 24.5384 |
| 0.0183 | 4.9254 | 330 | 0.5449 | 25.0953 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1