metadata
language:
- ro
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Tiny RO - Georgescu Dumitru
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_11_0
config: ro
split: None
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 37.72910622036657
Whisper Tiny RO - Georgescu Dumitru
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4606
- Wer: 37.7291
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-08
- 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: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
11.2437 | 1.7986 | 1000 | 0.4601 | 37.6053 |
10.9474 | 3.5971 | 2000 | 0.4602 | 37.0002 |
10.736 | 5.3957 | 3000 | 0.4604 | 37.5310 |
10.6145 | 7.1942 | 4000 | 0.4605 | 37.7114 |
10.5325 | 8.9928 | 5000 | 0.4606 | 37.7291 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1