metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-final
results: []
whisper-tiny-final
This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0714
- Wer: 6.3947
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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7273 | 1.6051 | 1000 | 0.7348 | 71.3477 |
| 0.392 | 3.2103 | 2000 | 0.4304 | 52.0592 |
| 0.3171 | 4.8154 | 3000 | 0.3059 | 39.7812 |
| 0.2064 | 6.4205 | 4000 | 0.2250 | 30.7857 |
| 0.1528 | 8.0257 | 5000 | 0.1694 | 23.0769 |
| 0.119 | 9.6308 | 6000 | 0.1304 | 16.5173 |
| 0.0823 | 11.2360 | 7000 | 0.1023 | 11.7556 |
| 0.0796 | 12.8411 | 8000 | 0.0852 | 8.5116 |
| 0.0514 | 14.4462 | 9000 | 0.0751 | 7.0490 |
| 0.045 | 16.0514 | 10000 | 0.0714 | 6.3947 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1