metadata
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Small Ro - Sarbu Vlad
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 18.664730616813383
Whisper Small Ro - Sarbu Vlad
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2920
- Wer: 18.6647
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
- num_devices: 3
- total_train_batch_size: 96
- total_eval_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1437 | 3.91 | 500 | 0.2167 | 20.5100 |
| 0.0268 | 7.81 | 1000 | 0.2202 | 18.6557 |
| 0.008 | 11.72 | 1500 | 0.2478 | 18.6829 |
| 0.0037 | 15.62 | 2000 | 0.2644 | 18.6708 |
| 0.0024 | 19.53 | 2500 | 0.2761 | 18.6405 |
| 0.0018 | 23.44 | 3000 | 0.2844 | 18.6859 |
| 0.0016 | 27.34 | 3500 | 0.2900 | 18.6799 |
| 0.0014 | 31.25 | 4000 | 0.2920 | 18.6647 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1