metadata
library_name: transformers
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Small En Medimix
results: []
Whisper Small En Medimix
This model is a fine-tuned version of openai/whisper-small on the 500 pes_colab 10.6 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4537
- Wer: 10.6667
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-06
- 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: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0384 | 1.0 | 25 | 0.4705 | 12.2222 |
| 0.0375 | 2.0 | 50 | 0.4689 | 12.0 |
| 0.0332 | 3.0 | 75 | 0.4666 | 11.0370 |
| 0.0293 | 4.0 | 100 | 0.4636 | 11.1111 |
| 0.0242 | 5.0 | 125 | 0.4612 | 11.0370 |
| 0.0197 | 6.0 | 150 | 0.4586 | 10.9630 |
| 0.0152 | 7.0 | 175 | 0.4555 | 10.7407 |
| 0.0116 | 8.0 | 200 | 0.4537 | 10.6667 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0