metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: sw
split: test
args: sw
metrics:
- name: Wer
type: wer
value: 23.724554196406032
openai/whisper-small
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6442
- Wer: 23.7246
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: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2694 | 1.07 | 1000 | 0.5438 | 26.8354 |
| 0.2306 | 3.02 | 2000 | 0.5081 | 23.9231 |
| 0.0467 | 4.09 | 3000 | 0.5648 | 24.4085 |
| 0.0239 | 6.03 | 4000 | 0.5994 | 23.8634 |
| 0.0123 | 7.1 | 5000 | 0.6442 | 23.7246 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3