metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- nyagen
metrics:
- wer
model-index:
- name: whisper-medium-nyagen-female-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nyagen
type: nyagen
metrics:
- name: Wer
type: wer
value: 0.25738585496866606
whisper-medium-nyagen-female-model
This model is a fine-tuned version of openai/whisper-medium on the nyagen dataset. It achieves the following results on the evaluation set:
- Loss: 0.3796
- Wer: 0.2574
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 |
|---|---|---|---|---|
| 1.1709 | 1.1834 | 200 | 0.6065 | 0.3997 |
| 0.4797 | 2.3669 | 400 | 0.4227 | 0.3908 |
| 0.2388 | 3.5503 | 600 | 0.3936 | 0.2932 |
| 0.1376 | 4.7337 | 800 | 0.3796 | 0.2574 |
| 0.0765 | 5.9172 | 1000 | 0.4010 | 0.2842 |
| 0.0344 | 7.1006 | 1200 | 0.4034 | 0.2381 |
| 0.0207 | 8.2840 | 1400 | 0.4384 | 0.2314 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0