| --- |
| language: |
| - ro |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| datasets: |
| - iulik-pisik/audio_vreme |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Base Romanian - Vreme Florin Busuioc |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Vreme ProTv - Florin Busuioc |
| type: iulik-pisik/audio_vreme |
| config: default |
| split: None |
| args: 'config: ro, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 13.206564209429539 |
| --- |
| |
| <!-- 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 Base Romanian - Vreme Florin Busuioc |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Vreme ProTv - Florin Busuioc dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2614 |
| - Wer: 13.2066 |
|
|
| ## 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: 4000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.0152 | 7.63 | 1000 | 0.1949 | 13.7015 | |
| | 0.0008 | 15.27 | 2000 | 0.2461 | 13.1545 | |
| | 0.0005 | 22.9 | 3000 | 0.2565 | 13.1024 | |
| | 0.0003 | 30.53 | 4000 | 0.2614 | 13.2066 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.39.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
| |
