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: ru
split: test
args: ru
metrics:
- name: Wer
type: wer
value: 12.29877024558306
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: 0.3157
- Wer: 12.2988
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 |
|---|---|---|---|---|
| 0.0731 | 1.04 | 1000 | 0.2183 | 13.0589 |
| 0.0194 | 3.02 | 2000 | 0.2390 | 12.8027 |
| 0.0067 | 4.06 | 3000 | 0.2524 | 12.5832 |
| 0.0025 | 6.04 | 4000 | 0.2725 | 12.3245 |
| 0.0017 | 8.02 | 5000 | 0.2854 | 12.7046 |
| 0.0009 | 9.06 | 6000 | 0.2915 | 12.5072 |
| 0.0005 | 11.04 | 7000 | 0.3006 | 12.2473 |
| 0.0004 | 13.02 | 8000 | 0.3060 | 12.2375 |
| 0.0003 | 14.06 | 9000 | 0.3129 | 12.2963 |
| 0.0003 | 16.04 | 10000 | 0.3157 | 12.2988 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2