metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-jp
results: []
whisper-small-jp
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6168
- Wer: 0.2600
- Cer: 0.2600
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 300
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.6589 | 1.0 | 7154 | 0.6615 | 0.2735 | 0.2735 |
| 0.6273 | 2.0 | 14308 | 0.6457 | 0.2699 | 0.2699 |
| 0.6251 | 3.0 | 21462 | 0.6359 | 0.2660 | 0.2660 |
| 0.6427 | 4.0 | 28616 | 0.6283 | 0.2642 | 0.2642 |
| 0.6389 | 5.0 | 35770 | 0.6243 | 0.2631 | 0.2631 |
| 0.6078 | 6.0 | 42924 | 0.6242 | 0.2615 | 0.2615 |
| 0.5788 | 7.0 | 50078 | 0.6195 | 0.2603 | 0.2603 |
| 0.5801 | 8.0 | 57232 | 0.6180 | 0.2596 | 0.2596 |
| 0.5866 | 9.0 | 64386 | 0.6145 | 0.2598 | 0.2598 |
| 0.6052 | 10.0 | 71540 | 0.6168 | 0.2600 | 0.2600 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0