metadata
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./949
results: []
./949
This model is a fine-tuned version of openai/whisper-large-v3 on the 949 FULL dataset. It achieves the following results on the evaluation set:
- Loss: 0.5601
- Wer Ortho: 29.5461
- Wer: 21.9669
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: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 1.0667 | 1.8692 | 100 | 0.7607 | 37.1700 | 28.4674 |
| 0.7153 | 3.7383 | 200 | 0.6157 | 32.8982 | 24.5167 |
| 0.5672 | 5.6075 | 300 | 0.5747 | 30.5251 | 22.3872 |
| 0.4809 | 7.4766 | 400 | 0.5630 | 29.4275 | 21.7428 |
| 0.428 | 9.3458 | 500 | 0.5601 | 29.5461 | 21.9669 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1