| --- |
| language: |
| - ate |
| license: apache-2.0 |
| base_model: openai/whisper-base |
| tags: |
| - whisper-event |
| - generated_from_trainer |
| datasets: |
| - tericlabs |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper base ateso |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Sunbird |
| type: tericlabs |
| metrics: |
| - name: Wer |
| type: wer |
| value: 27.710843373493976 |
| --- |
| |
| <!-- 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 ateso |
|
|
| This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Sunbird dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5293 |
| - Wer: 27.7108 |
|
|
| ## 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: 1000 |
| - training_steps: 5000 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.4597 | 3.5 | 1000 | 0.5186 | 32.1285 | |
| | 0.1812 | 6.99 | 2000 | 0.4394 | 26.7738 | |
| | 0.0429 | 10.49 | 3000 | 0.4765 | 26.7738 | |
| | 0.016 | 13.99 | 4000 | 0.5157 | 27.3092 | |
| | 0.0053 | 17.48 | 5000 | 0.5293 | 27.7108 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.0.dev0 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
| |
