metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bigcgen-female-5hrs-62
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bigcgen
type: bigcgen
metrics:
- name: Wer
type: wer
value: 0.548921679909194
whisper-medium-bigcgen-female-5hrs-62
This model is a fine-tuned version of openai/whisper-medium on the bigcgen dataset. It achieves the following results on the evaluation set:
- Loss: 0.7278
- Wer: 0.5489
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: 62
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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 |
|---|---|---|---|---|
| 1.0539 | 0.5984 | 200 | 1.0387 | 0.6708 |
| 0.7105 | 1.1945 | 400 | 0.8432 | 0.5764 |
| 0.6344 | 1.7928 | 600 | 0.7586 | 0.5600 |
| 0.5221 | 2.3889 | 800 | 0.7457 | 0.5623 |
| 0.4151 | 2.9873 | 1000 | 0.7278 | 0.5489 |
| 0.219 | 3.5834 | 1200 | 0.7980 | 0.5287 |
| 0.1226 | 4.1795 | 1400 | 0.8193 | 0.5362 |
| 0.1245 | 4.7779 | 1600 | 0.8030 | 0.4976 |
| 0.0529 | 5.3740 | 1800 | 0.8765 | 0.4963 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0