metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: fs-w-xavier-base
results: []
fs-w-xavier-base
This model is a fine-tuned version of openai/whisper-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3748
- Wer: 90.8832
- Cer: 69.2460
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
3.8293 | 4.5872 | 500 | 3.9014 | 98.4330 | 73.8234 |
0.9253 | 9.1743 | 1000 | 1.1787 | 101.2821 | 77.9887 |
0.3997 | 13.7615 | 1500 | 0.6684 | 98.9079 | 76.8980 |
0.3313 | 18.3486 | 2000 | 0.4931 | 97.4359 | 79.5259 |
0.2974 | 22.9358 | 2500 | 0.4656 | 109.0693 | 83.0385 |
0.2635 | 27.5229 | 3000 | 0.4219 | 103.5138 | 78.6843 |
0.2241 | 32.1101 | 3500 | 0.4047 | 100.5698 | 77.2587 |
0.1939 | 36.6972 | 4000 | 0.3893 | 89.9810 | 69.3404 |
0.1718 | 41.2844 | 4500 | 0.3807 | 87.8443 | 67.3738 |
0.1471 | 45.8716 | 5000 | 0.3748 | 90.8832 | 69.2460 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0