metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- yashtiwari/PaulMooney-Medical-ASR-Data
metrics:
- wer
model-index:
- name: Whisper Dr Patient Conversation
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Medical ASR
type: yashtiwari/PaulMooney-Medical-ASR-Data
metrics:
- type: wer
value: 21.313058170407917
name: Wer
Whisper Dr Patient Conversation
This model is a fine-tuned version of openai/whisper-medium on the Medical ASR dataset. It achieves the following results on the evaluation set:
- Loss: 0.0967
- Wer: 21.3131
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6737 | 0.1357 | 100 | 0.2638 | 14.9650 |
| 0.212 | 0.2714 | 200 | 0.1960 | 11.7789 |
| 0.2321 | 0.4071 | 300 | 0.1506 | 14.8202 |
| 0.1462 | 0.5427 | 400 | 0.1126 | 18.3683 |
| 0.1419 | 0.6784 | 500 | 0.0967 | 21.3131 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3