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-baseline-model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: bigcgen
type: bigcgen
metrics:
- name: Wer
type: wer
value: 0.5197446204776542
whisper-medium-bigcgen-baseline-model
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: 0.6934
- Wer: 0.5197
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 |
|---|---|---|---|---|
| 4.3168 | 0.6102 | 200 | 0.9403 | 0.6505 |
| 2.7179 | 1.2227 | 400 | 0.7717 | 0.5571 |
| 2.4784 | 1.8330 | 600 | 0.7120 | 0.5119 |
| 1.6451 | 2.4455 | 800 | 0.6934 | 0.5197 |
| 0.9938 | 3.0580 | 1000 | 0.7158 | 0.4881 |
| 0.9703 | 3.6682 | 1200 | 0.7220 | 0.5018 |
| 0.5808 | 4.2807 | 1400 | 0.7521 | 0.4930 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0