metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bsbigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bsbigcgen-male-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bsbigcgen
type: bsbigcgen
metrics:
- name: Wer
type: wer
value: 0.5177174413253567
whisper-medium-bsbigcgen-male-model
This model is a fine-tuned version of openai/whisper-medium on the bsbigcgen dataset. It achieves the following results on the evaluation set:
- Loss: 0.6923
- Wer: 0.5177
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
- num_epochs: 30.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.039 | 0.6421 | 200 | 0.9764 | 0.6942 |
| 2.6473 | 1.2825 | 400 | 0.7705 | 0.5812 |
| 2.3913 | 1.9246 | 600 | 0.7010 | 0.5269 |
| 1.6283 | 2.5650 | 800 | 0.6923 | 0.5177 |
| 0.7783 | 3.2055 | 1000 | 0.7241 | 0.5131 |
| 0.8723 | 3.8475 | 1200 | 0.7207 | 0.5140 |
| 0.3633 | 4.4880 | 1400 | 0.7590 | 0.4961 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0