metadata
language:
- bg
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Bg - Yonchevisky_tes2t
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: bg
split: test
args: 'config: hi, split: test'
metrics:
- name: Wer
type: wer
value: 61.83524504692388
Whisper Small Bg - Yonchevisky_tes2t
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7377
- Wer: 61.8352
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.8067 | 0.37 | 100 | 1.6916 | 137.6897 |
| 0.9737 | 0.73 | 200 | 1.1197 | 78.3571 |
| 0.7747 | 1.1 | 300 | 0.9763 | 73.8906 |
| 0.6672 | 1.47 | 400 | 0.8972 | 70.7102 |
| 0.6196 | 1.84 | 500 | 0.8329 | 67.4545 |
| 0.4849 | 2.21 | 600 | 0.7968 | 66.6029 |
| 0.4402 | 2.57 | 700 | 0.7597 | 62.7795 |
| 0.4601 | 2.94 | 800 | 0.7385 | 61.8642 |
| 0.3545 | 3.31 | 900 | 0.7394 | 61.5050 |
| 0.3596 | 3.68 | 1000 | 0.7377 | 61.8352 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2