metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- nyansapo_ai-asr-leaderboard
- generated_from_trainer
datasets:
- NyansapoAI/azure-dataset
metrics:
- wer
model-index:
- name: whisper-base-bungoma.en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Azure-dataset
type: NyansapoAI/azure-dataset
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 25.28041415012942
whisper-base-bungoma.en
This model is a fine-tuned version of openai/whisper-base.en on the Azure-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0636
- Wer: 25.2804
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: 250
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.7399 | 1.38 | 250 | 0.2390 | 29.3356 |
0.2829 | 2.76 | 500 | 0.0774 | 21.8292 |
0.1573 | 4.14 | 750 | 0.0921 | 22.8645 |
0.1373 | 5.52 | 1000 | 0.0636 | 25.2804 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2