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-nyagen-combined-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bemgen
type: bemgen
metrics:
- name: Wer
type: wer
value: 0.19520264681555005
whisper-medium-nyagen-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: 0.2561
- Wer: 0.1952
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 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 |
|---|---|---|---|---|
| 1.1602 | 0.5326 | 200 | 0.5182 | 0.3747 |
| 0.5456 | 1.0639 | 400 | 0.3445 | 0.2552 |
| 0.5516 | 1.5965 | 600 | 0.2903 | 0.2413 |
| 0.224 | 2.1278 | 800 | 0.2817 | 0.2384 |
| 0.2413 | 2.6605 | 1000 | 0.2561 | 0.1952 |
| 0.1036 | 3.1917 | 1200 | 0.2583 | 0.1904 |
| 0.1135 | 3.7244 | 1400 | 0.2637 | 0.2120 |
| 0.057 | 4.2557 | 1600 | 0.2731 | 0.2097 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0