metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: l3-whisper-medium-l3c3_e1_v7
results: []
l3-whisper-medium-l3c3_e1_v7
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: 0.3650
- Wer: 13.5596
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2112 | 0.0927 | 3000 | 0.4719 | 22.7174 |
| 0.1775 | 0.1854 | 6000 | 0.4478 | 19.2846 |
| 0.16 | 0.2782 | 9000 | 0.4300 | 17.8644 |
| 0.1499 | 0.3709 | 12000 | 0.4118 | 16.7179 |
| 0.1429 | 0.4636 | 15000 | 0.3920 | 15.8724 |
| 0.1354 | 0.5563 | 18000 | 0.3749 | 15.3029 |
| 0.1317 | 0.6490 | 21000 | 0.3774 | 15.0261 |
| 0.1279 | 0.7417 | 24000 | 0.3668 | 14.1700 |
| 0.1247 | 0.8345 | 27000 | 0.3704 | 13.8788 |
| 0.1213 | 0.9272 | 30000 | 0.3650 | 13.5596 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.4.1+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4