metadata
language:
- bg
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: whisper-small-bg
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_13_0 bg
type: mozilla-foundation/common_voice_13_0
config: bg
split: test
args: bg
metrics:
- name: Wer
type: wer
value: 44.67291341315287
whisper-small-bg
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 bg dataset. It achieves the following results on the evaluation set:
- Loss: 9.0612
- Wer: 44.6729
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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.9319 | 6.76 | 1000 | 10.0774 | 73.9892 |
| 2.6116 | 13.51 | 2000 | 11.4089 | 67.0484 |
| 0.9607 | 20.27 | 3000 | 11.8266 | 60.9448 |
| 0.3464 | 27.03 | 4000 | 9.9500 | 52.1213 |
| 0.0122 | 33.78 | 5000 | 9.0612 | 44.6729 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3