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---
language:
- ro
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Large_v2 RO CV17
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 47.51015670342426
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Whisper Large_v2 RO CV17
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6152
- Wer: 47.5102
## 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5004 | 5.4945 | 1000 | 1.1554 | 106.2565 |
| 0.0896 | 10.9890 | 2000 | 1.3810 | 51.0737 |
| 0.0121 | 16.4835 | 3000 | 1.5371 | 49.9013 |
| 0.0027 | 21.9780 | 4000 | 1.5901 | 49.1468 |
| 0.0008 | 27.4725 | 5000 | 1.6152 | 47.5102 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.19.1
|