metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-ken
results: []
whisper-small-ken
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 1.9940
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: 0.0004
- 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: linear
- lr_scheduler_warmup_steps: 132
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.3889 | 1.3889 | 100 | 0.2292 | 79.2622 |
0.2621 | 2.7778 | 200 | 0.1175 | 18.3450 |
0.1632 | 4.1667 | 300 | 0.0784 | 14.6062 |
0.1054 | 5.5556 | 400 | 0.0422 | 7.2782 |
0.0844 | 6.9444 | 500 | 0.0443 | 9.9202 |
0.0666 | 8.3333 | 600 | 0.0581 | 15.2044 |
0.0522 | 9.7222 | 700 | 0.0490 | 10.1695 |
0.0504 | 11.1111 | 800 | 0.0586 | 9.1725 |
0.0365 | 12.5 | 900 | 0.0386 | 12.7617 |
0.0336 | 13.8889 | 1000 | 0.0224 | 13.5593 |
0.0244 | 15.2778 | 1100 | 0.0138 | 7.3280 |
0.0177 | 16.6667 | 1200 | 0.0191 | 5.0349 |
0.0143 | 18.0556 | 1300 | 0.0050 | 5.7328 |
0.007 | 19.4444 | 1400 | 0.0014 | 1.9940 |
0.0018 | 20.8333 | 1500 | 0.0001 | 2.6421 |
0.0003 | 22.2222 | 1600 | 0.0000 | 1.9940 |
0.0 | 23.6111 | 1700 | 0.0000 | 1.9940 |
0.0 | 25.0 | 1800 | 0.0000 | 1.9940 |
0.0 | 26.3889 | 1900 | 0.0000 | 1.9940 |
0.0 | 27.7778 | 2000 | 0.0000 | 1.9940 |
0.0 | 29.1667 | 2100 | 0.0000 | 1.9940 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1