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-baseline-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bemgen
type: bemgen
metrics:
- name: Wer
type: wer
value: 0.40704164877629884
whisper-medium-bemgen-baseline-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: 0.5039
- Wer: 0.4070
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 |
|---|---|---|---|---|
| 3.7384 | 0.3960 | 200 | 0.9033 | 0.6956 |
| 3.0032 | 0.7921 | 400 | 0.6777 | 0.5601 |
| 1.9783 | 1.1881 | 600 | 0.5935 | 0.4839 |
| 1.7382 | 1.5842 | 800 | 0.5463 | 0.4397 |
| 1.7106 | 1.9802 | 1000 | 0.5039 | 0.4070 |
| 0.8331 | 2.3762 | 1200 | 0.5411 | 0.4137 |
| 0.8928 | 2.7723 | 1400 | 0.5324 | 0.4012 |
| 0.3736 | 3.1683 | 1600 | 0.5273 | 0.3802 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0