metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4
results: []
whisper-large-v3-cit-do015-wd0-lr1e-06-FULL4
This model is a fine-tuned version of openai/whisper-large-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5059
- Wer Ortho: 28.4797
- Wer: 21.0751
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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 1400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.9206 | 0.7715 | 200 | 0.6309 | 33.9104 | 25.9900 |
| 0.6533 | 1.5429 | 400 | 0.5581 | 30.2736 | 22.5910 |
| 0.5875 | 2.3144 | 600 | 0.5322 | 29.5128 | 22.8648 |
| 0.5351 | 3.0858 | 800 | 0.5176 | 29.3103 | 21.8431 |
| 0.5126 | 3.8573 | 1000 | 0.5112 | 28.7100 | 21.3222 |
| 0.4956 | 4.6287 | 1200 | 0.5063 | 28.6053 | 21.0751 |
| 0.4785 | 5.4002 | 1400 | 0.5059 | 28.4797 | 21.0751 |
Framework versions
- Transformers 4.45.1
- Pytorch 1.13.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0