metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- suhaibmasood/med-audio-3
metrics:
- wer
model-index:
- name: Whisper Small en-Harpreet Singh
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: med-audio-3
type: suhaibmasood/med-audio-3
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 12.560386473429952
Whisper Small en-Harpreet Singh
This model is a fine-tuned version of openai/whisper-medium on the med-audio-3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0384
- Wer: 12.5604
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: 1
- eval_batch_size: 2
- seed: 42
- 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: 100
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0221 | 0.3268 | 100 | 0.0383 | 13.1643 |
| 0.0339 | 0.6536 | 200 | 0.0373 | 13.0435 |
| 0.0265 | 0.9804 | 300 | 0.0382 | 12.9227 |
| 0.0048 | 1.3072 | 400 | 0.0388 | 13.0435 |
| 0.0088 | 1.6340 | 500 | 0.0384 | 12.5604 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3