metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-jp
results: []
whisper-medium-jp
This model is a fine-tuned version of openai/whisper-medium on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4828
- Wer: 0.2254
- Cer: 0.2254
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: 4e-06
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- 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: 400
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.5341 | 1.0 | 7155 | 0.5321 | 0.2416 | 0.2416 |
| 0.5023 | 2.0 | 14310 | 0.5143 | 0.2369 | 0.2369 |
| 0.499 | 3.0 | 21465 | 0.5063 | 0.2337 | 0.2337 |
| 0.4773 | 4.0 | 28620 | 0.5010 | 0.2310 | 0.2310 |
| 0.4775 | 5.0 | 35775 | 0.4944 | 0.2289 | 0.2289 |
| 0.4709 | 6.0 | 42930 | 0.4886 | 0.2288 | 0.2288 |
| 0.4907 | 7.0 | 50085 | 0.4870 | 0.2271 | 0.2271 |
| 0.4855 | 8.0 | 57240 | 0.4868 | 0.2261 | 0.2261 |
| 0.4487 | 9.0 | 64395 | 0.4828 | 0.2254 | 0.2254 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.0