metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- swagen
metrics:
- wer
model-index:
- name: whisper-medium-swagen-baseline-62
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: swagen
type: swagen
metrics:
- name: Wer
type: wer
value: 0.3235867446393762
whisper-medium-swagen-baseline-62
This model is a fine-tuned version of openai/whisper-medium on the swagen dataset. It achieves the following results on the evaluation set:
- Loss: 0.5485
- Wer: 0.3236
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 |
|---|---|---|---|---|
| 0.7072 | 0.4759 | 200 | 0.8145 | 0.4739 |
| 0.5449 | 0.9518 | 400 | 0.6483 | 0.4019 |
| 0.3228 | 1.4259 | 600 | 0.5974 | 0.3901 |
| 0.2807 | 1.9018 | 800 | 0.5491 | 0.3579 |
| 0.1053 | 2.3760 | 1000 | 0.5588 | 0.4012 |
| 0.1212 | 2.8519 | 1200 | 0.5485 | 0.3236 |
| 0.044 | 3.3260 | 1400 | 0.5706 | 0.3248 |
| 0.0578 | 3.8019 | 1600 | 0.5690 | 0.3924 |
| 0.0227 | 4.2760 | 1800 | 0.5783 | 0.3152 |
| 0.0201 | 4.7519 | 2000 | 0.5821 | 0.2834 |
Framework versions
- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0