metadata
language:
- mn
license: apache-2.0
base_model: zagibest/whisper-small-custom-data
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: Whisper Small MN with custom data + Common voice + Google Fluers - Zagi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: mn_mn
split: None
args: 'config: mn, split: test'
metrics:
- name: Wer
type: wer
value: 34.56211146253681
Whisper Small MN with custom data + Common voice + Google Fluers - Zagi
This model is a fine-tuned version of zagibest/whisper-small-custom-data on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5343
- Wer: 34.5621
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: 8
- 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: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1792 | 2.59 | 500 | 0.4204 | 38.2103 |
| 0.0121 | 5.18 | 1000 | 0.4673 | 36.5634 |
| 0.0034 | 7.77 | 1500 | 0.4964 | 35.6309 |
| 0.0009 | 10.36 | 2000 | 0.5044 | 34.7366 |
| 0.0007 | 12.95 | 2500 | 0.5166 | 34.7366 |
| 0.0004 | 15.54 | 3000 | 0.5271 | 34.5785 |
| 0.0003 | 18.13 | 3500 | 0.5323 | 34.5948 |
| 0.0003 | 20.73 | 4000 | 0.5343 | 34.5621 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2