metadata
language:
- en
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small English
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 en
type: mozilla-foundation/common_voice_11_0
config: en
split: test
args: en
metrics:
- type: wer
value: 13.058509783761204
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: en_us
split: test
metrics:
- type: wer
value: 9.27
name: WER
Whisper Small English
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 en dataset. It achieves the following results on the evaluation set:
- Loss: 0.3269
- Wer: 13.0585
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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1537 | 0.1 | 1000 | 0.4405 | 17.9276 |
| 0.2378 | 0.2 | 2000 | 0.4009 | 15.9888 |
| 0.1709 | 0.3 | 3000 | 0.3852 | 15.4953 |
| 0.2792 | 0.4 | 4000 | 0.3699 | 14.8758 |
| 0.2172 | 0.5 | 5000 | 0.3577 | 14.2660 |
| 0.3616 | 0.6 | 6000 | 0.4042 | 18.1846 |
| 0.2456 | 0.7 | 7000 | 0.3375 | 13.3091 |
| 0.2505 | 0.8 | 8000 | 0.3395 | 13.6227 |
| 0.2563 | 0.9 | 9000 | 0.3305 | 13.1408 |
| 0.2395 | 1.0 | 10000 | 0.3269 | 13.0585 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2