metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- nyansapo_ai-asr-leaderboard
- generated_from_trainer
datasets:
- NyansapoAI/azure-dataset
metrics:
- wer
model-index:
- name: whisper-tiny.en
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Azure-dataset
type: NyansapoAI/azure-dataset
config: default
split: test
args: 'split: test'
metrics:
- name: Wer
type: wer
value: 2.8282828282828283
whisper-tiny.en
This model is a fine-tuned version of openai/whisper-tiny.en on the Azure-dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0201
- Wer: 2.8283
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.075 | 6.21 | 1000 | 0.0254 | 2.2222 |
| 0.0472 | 12.42 | 2000 | 0.0195 | 1.6162 |
| 0.0419 | 18.63 | 3000 | 0.0204 | 2.2222 |
| 0.0425 | 24.84 | 4000 | 0.0201 | 2.8283 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3