metadata
language:
- ro
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_romanian_speech_synthesis
metrics:
- wer
model-index:
- name: Whisper Medium Ro - Sarbu Vlad - multi gpu
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1 + Romanian speech synthesis
type: VladS159/common_voice_romanian_speech_synthesis
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 11.726235741444867
Whisper Medium Ro - Sarbu Vlad - multi gpu
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.1 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:
- Loss: 0.1247
- Wer: 11.7262
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: 10
- eval_batch_size: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 30
- total_eval_batch_size: 30
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1447 | 0.61 | 250 | 0.1532 | 13.8768 |
| 0.0599 | 1.23 | 500 | 0.1305 | 12.5141 |
| 0.0595 | 1.84 | 750 | 0.1256 | 12.3255 |
| 0.032 | 2.46 | 1000 | 0.1247 | 11.7262 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1