metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- domain-asr
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: Whisper
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: immunology dataset
type: audiofolder
config: default
split: test
args: 'config: en, split: test'
metrics:
- name: Wer
type: wer
value: 10.52827380952381
Whisper
This model is a fine-tuned version of openai/whisper-small on the immunology dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3409
- Wer: 10.5283
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0305 | 4.55 | 1000 | 0.2471 | 11.1359 |
| 0.0117 | 9.09 | 2000 | 0.3168 | 10.3795 |
| 0.0024 | 13.64 | 3000 | 0.3312 | 10.4291 |
| 0.0006 | 18.18 | 4000 | 0.3409 | 10.5283 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0