metadata
language:
- ro
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- VladS159/common_voice_17_0_romanian_speech_synthesis
metrics:
- wer
model-index:
- name: Whisper Small Ro - Sarbu Vlad - multi gpu --> 3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0 + Romanian speech synthesis
type: VladS159/common_voice_17_0_romanian_speech_synthesis
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 10.55709542810149
Whisper Small Ro - Sarbu Vlad - multi gpu --> 3
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 + Romanian speech synthesis dataset. It achieves the following results on the evaluation set:
- Loss: 0.1249
- Wer: 10.5571
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: 10
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- total_train_batch_size: 48
- 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: 600
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2432 | 0.68 | 500 | 0.2134 | 19.7435 |
| 0.137 | 1.36 | 1000 | 0.1532 | 15.5189 |
| 0.0672 | 2.04 | 1500 | 0.1287 | 13.0426 |
| 0.0579 | 2.72 | 2000 | 0.1218 | 12.8659 |
| 0.0307 | 3.4 | 2500 | 0.1183 | 11.9887 |
| 0.0167 | 4.08 | 3000 | 0.1177 | 11.5866 |
| 0.016 | 4.76 | 3500 | 0.1149 | 10.9531 |
| 0.0099 | 5.43 | 4000 | 0.1212 | 10.9713 |
| 0.0058 | 6.11 | 4500 | 0.1216 | 10.8251 |
| 0.0056 | 6.79 | 5000 | 0.1224 | 10.6515 |
| 0.0036 | 7.47 | 5500 | 0.1238 | 10.6211 |
| 0.0035 | 8.15 | 6000 | 0.1249 | 10.5571 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.1