metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- asr-fyp
- generated_from_trainer
datasets:
- AshtonLKY/Whisper_ASR_ATC
metrics:
- wer
model-index:
- name: Whisper_ASR_ATC
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: AshtonLKY/augmented_audio
type: AshtonLKY/Whisper_ASR_ATC
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 10.259091588129461
Whisper_ASR_ATC
This model is a fine-tuned version of openai/whisper-small on the AshtonLKY/augmented_audio dataset. It achieves the following results on the evaluation set:
- Loss: 0.0171
- Wer: 10.2591
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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2282 | 0.3 | 1000 | 0.2253 | 49.5224 |
| 0.1461 | 0.6 | 2000 | 0.1456 | 42.3271 |
| 0.1052 | 0.89 | 3000 | 0.1061 | 10.8325 |
| 0.0698 | 1.19 | 4000 | 0.0708 | 13.8258 |
| 0.043 | 1.49 | 5000 | 0.0537 | 11.0072 |
| 0.0407 | 1.79 | 6000 | 0.0383 | 10.9401 |
| 0.019 | 2.08 | 7000 | 0.0349 | 15.2078 |
| 0.0323 | 2.38 | 8000 | 0.0268 | 11.4068 |
| 0.0164 | 2.68 | 9000 | 0.0236 | 12.3902 |
| 0.0153 | 2.98 | 10000 | 0.0171 | 10.2591 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0