metadata
base_model: openai/whisper-large-v3
library_name: transformers
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-genbed-m-model
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: genbed
type: genbed
config: en
split: test
metrics:
- type: wer
value: 37.19
name: WER
whisper-large-v3-genbed-m-model
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7479
- Wer: 36.9425
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: 1.75e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 30000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.4385 | 0.6596 | 250 | 0.7026 | 57.3435 |
| 0.578 | 1.3193 | 500 | 0.6312 | 47.4271 |
| 0.499 | 1.9789 | 750 | 0.5735 | 43.2676 |
| 0.2829 | 2.6385 | 1000 | 0.5949 | 41.0913 |
| 0.2304 | 3.2982 | 1250 | 0.6149 | 40.5660 |
| 0.1672 | 3.9578 | 1500 | 0.5645 | 38.5399 |
| 0.1019 | 4.6174 | 1750 | 0.6265 | 42.0026 |
| 0.0911 | 5.2770 | 2000 | 0.6534 | 38.5399 |
| 0.0713 | 5.9367 | 2250 | 0.6533 | 38.1754 |
| 0.0545 | 6.5963 | 2500 | 0.6577 | 37.7466 |
| 0.0497 | 7.2559 | 2750 | 0.6626 | 39.3117 |
| 0.0425 | 7.9156 | 3000 | 0.6901 | 37.2642 |
| 0.0374 | 8.5752 | 3250 | 0.6919 | 38.6256 |
| 0.0312 | 9.2348 | 3500 | 0.7093 | 37.2856 |
| 0.0302 | 9.8945 | 3750 | 0.7260 | 35.7740 |
| 0.0233 | 10.5541 | 4000 | 0.7181 | 36.5780 |
| 0.0262 | 11.2137 | 4250 | 0.7352 | 35.5703 |
| 0.0241 | 11.8734 | 4500 | 0.7340 | 36.4172 |
| 0.0198 | 12.5330 | 4750 | 0.7463 | 36.8461 |
| 0.0201 | 13.1926 | 5000 | 0.7479 | 36.9425 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1