metadata
license: apache-2.0
tags:
- generated_from_trainer
base_model: openai/whisper-large-v2
metrics:
- wer
model-index:
- name: BA_Model_V3
results: []
BA_Model_V3
This model is a fine-tuned version of openai/whisper-large-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3495
- Wer: 21.1224
- Cer: 12.2080
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.0358 | 1.0 | 278 | 0.6770 | 23.3686 | 13.9275 |
| 0.2753 | 2.0 | 556 | 0.3313 | 20.7071 | 12.0535 |
| 0.2109 | 3.0 | 834 | 0.3098 | 20.7204 | 12.1752 |
| 0.1603 | 4.0 | 1112 | 0.3129 | 20.4645 | 11.8444 |
| 0.1224 | 5.0 | 1390 | 0.3242 | 20.8034 | 12.0535 |
| 0.0956 | 6.0 | 1668 | 0.3353 | 20.7802 | 11.9894 |
| 0.0781 | 7.0 | 1946 | 0.3464 | 21.0659 | 12.1725 |
| 0.0716 | 8.0 | 2224 | 0.3495 | 21.1224 | 12.2080 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2