metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bemgen
metrics:
- wer
model-index:
- name: whisper-medium-bemgen-combined-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bemgen
type: bemgen
metrics:
- name: Wer
type: wer
value: 0.3331540447504303
whisper-medium-bemgen-combined-model
This model is a fine-tuned version of openai/whisper-medium on the bemgen dataset. It achieves the following results on the evaluation set:
- Loss: 0.4200
- Wer: 0.3332
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7922 | 0.1980 | 200 | 0.8807 | 0.6663 |
| 1.3451 | 0.3960 | 400 | 0.6738 | 0.5310 |
| 1.1869 | 0.5941 | 600 | 0.5800 | 0.4613 |
| 0.9659 | 0.7921 | 800 | 0.5199 | 0.4211 |
| 0.8946 | 0.9901 | 1000 | 0.4816 | 0.3967 |
| 0.6349 | 1.1881 | 1200 | 0.4725 | 0.3726 |
| 0.6238 | 1.3861 | 1400 | 0.4549 | 0.3603 |
| 0.6244 | 1.5842 | 1600 | 0.4495 | 0.3648 |
| 0.5724 | 1.7822 | 1800 | 0.4362 | 0.3451 |
| 0.6594 | 1.9802 | 2000 | 0.4200 | 0.3332 |
| 0.3207 | 2.1782 | 2200 | 0.4395 | 0.3353 |
| 0.301 | 2.3762 | 2400 | 0.4479 | 0.3275 |
| 0.2863 | 2.5743 | 2600 | 0.4369 | 0.3358 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0