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-100f50m-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bemgen
type: bemgen
metrics:
- name: Wer
type: wer
value: 0.38982326111744586
whisper-medium-bemgen-100f50m-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: 0.4354
- Wer: 0.3898
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use 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 |
|---|---|---|---|---|
| 3.1512 | 0.2641 | 200 | 0.8282 | 0.6534 |
| 2.4008 | 0.5282 | 400 | 0.6203 | 0.5097 |
| 2.2459 | 0.7923 | 600 | 0.5506 | 0.4644 |
| 1.3319 | 1.0555 | 800 | 0.5029 | 0.4017 |
| 1.5588 | 1.3196 | 1000 | 0.4675 | 0.3897 |
| 1.2908 | 1.5837 | 1200 | 0.4534 | 0.3727 |
| 1.4258 | 1.8478 | 1400 | 0.4354 | 0.3898 |
| 0.6383 | 2.1109 | 1600 | 0.4480 | 0.3600 |
| 0.6079 | 2.3750 | 1800 | 0.4444 | 0.3482 |
| 0.5709 | 2.6392 | 2000 | 0.4367 | 0.3405 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0