| | --- |
| | library_name: transformers |
| | language: |
| | - en |
| | license: apache-2.0 |
| | base_model: openai/whisper-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | - precision |
| | - recall |
| | - f1 |
| | model-index: |
| | - name: ./whisper-base-ea_5hr |
| | results: [] |
| | --- |
| | |
| | <!-- 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-ea_5hr |
| | |
| | This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Afrispeech-200 dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7154 |
| | - Wer Ortho: 0.2898 |
| | - Wer: 0.2319 |
| | - Cer: 0.1088 |
| | - Precision: 0.8599 |
| | - Recall: 0.8590 |
| | - F1: 0.8585 |
| | |
| | ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: constant_with_warmup |
| | - lr_scheduler_warmup_steps: 50 |
| | - training_steps: 500 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | Cer | Precision | Recall | F1 | |
| | |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------:|:------:|:------:| |
| | | 0.9173 | 0.2364 | 100 | 0.9484 | 0.3210 | 0.2633 | 0.1182 | 0.8389 | 0.8419 | 0.8398 | |
| | | 0.8464 | 0.4728 | 200 | 0.8059 | 0.2924 | 0.2312 | 0.1026 | 0.8519 | 0.8523 | 0.8515 | |
| | | 0.7615 | 0.7092 | 300 | 0.7548 | 0.2925 | 0.2340 | 0.1048 | 0.8557 | 0.8556 | 0.8550 | |
| | | 0.7301 | 0.9456 | 400 | 0.7282 | 0.2877 | 0.2288 | 0.1030 | 0.8603 | 0.8613 | 0.8602 | |
| | | 0.5936 | 1.1820 | 500 | 0.7154 | 0.2898 | 0.2319 | 0.1088 | 0.8599 | 0.8590 | 0.8585 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.51.3 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.1 |
| |
|
