metadata
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-small-bn
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: bn
split: test
args: bn
metrics:
- name: Wer
type: wer
value: 31.772098978338693
whisper-small-bn
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: 0.1134
- Wer: 31.7721
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2262 | 0.3183 | 500 | 0.2355 | 61.4003 |
| 0.1542 | 0.6365 | 1000 | 0.1628 | 47.9933 |
| 0.1166 | 0.9548 | 1500 | 0.1391 | 43.0509 |
| 0.0803 | 1.2731 | 2000 | 0.1252 | 38.7278 |
| 0.0793 | 1.5913 | 2500 | 0.1147 | 36.4728 |
| 0.0834 | 1.9096 | 3000 | 0.1079 | 34.6947 |
| 0.0463 | 2.2279 | 3500 | 0.1097 | 33.4679 |
| 0.0541 | 2.5461 | 4000 | 0.1084 | 32.9231 |
| 0.0487 | 2.8644 | 4500 | 0.1042 | 32.5743 |
| 0.0281 | 3.1827 | 5000 | 0.1136 | 32.6657 |
| 0.0313 | 3.5010 | 5500 | 0.1127 | 32.2032 |
| 0.0286 | 3.8192 | 6000 | 0.1134 | 31.7721 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1