metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium.en
results: []
whisper-medium.en
This model is a fine-tuned version of openai/whisper-medium.en on an acc_dataset_v3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4242
- Wer: 0.1293
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
See the training notebook here:
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- optimizer: Use 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: 25
- training_steps: 300
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.6045 | 2.2727 | 25 | 0.9047 | 0.1535 |
| 0.2267 | 4.5455 | 50 | 0.4149 | 0.1262 |
| 0.0207 | 6.8182 | 75 | 0.4454 | 0.1483 |
| 0.0134 | 9.0909 | 100 | 0.4660 | 0.1388 |
| 0.009 | 11.3636 | 125 | 0.4311 | 0.1462 |
| 0.0051 | 13.6364 | 150 | 0.4368 | 0.1356 |
| 0.0018 | 15.9091 | 175 | 0.4294 | 0.1462 |
| 0.0003 | 18.1818 | 200 | 0.4234 | 0.1356 |
| 0.0002 | 20.4545 | 225 | 0.4235 | 0.1325 |
| 0.0002 | 22.7273 | 250 | 0.4239 | 0.1304 |
| 0.0002 | 25.0 | 275 | 0.4240 | 0.1283 |
| 0.0002 | 27.2727 | 300 | 0.4242 | 0.1293 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0