metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: torgo_tiny_finetune_M03
results: []
torgo_tiny_finetune_M03
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3315
- Wer: 28.3531
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6365 | 0.85 | 500 | 0.3228 | 25.3820 |
| 0.1068 | 1.71 | 1000 | 0.3417 | 52.2920 |
| 0.1009 | 2.56 | 1500 | 0.3318 | 48.2173 |
| 0.0686 | 3.41 | 2000 | 0.2947 | 30.3056 |
| 0.0516 | 4.27 | 2500 | 0.3396 | 26.0611 |
| 0.0353 | 5.12 | 3000 | 0.3153 | 28.4380 |
| 0.0255 | 5.97 | 3500 | 0.2689 | 24.7878 |
| 0.0207 | 6.83 | 4000 | 0.4144 | 35.1443 |
| 0.0148 | 7.68 | 4500 | 0.2552 | 31.8336 |
| 0.015 | 8.53 | 5000 | 0.3356 | 32.5127 |
| 0.0114 | 9.39 | 5500 | 0.3311 | 32.9372 |
| 0.0098 | 10.24 | 6000 | 0.3318 | 24.4482 |
| 0.0067 | 11.09 | 6500 | 0.2942 | 29.5416 |
| 0.0031 | 11.95 | 7000 | 0.3945 | 60.8659 |
| 0.0044 | 12.8 | 7500 | 0.3343 | 28.5229 |
| 0.0026 | 13.65 | 8000 | 0.3204 | 23.3447 |
| 0.0019 | 14.51 | 8500 | 0.3103 | 24.6180 |
| 0.001 | 15.36 | 9000 | 0.3257 | 29.6265 |
| 0.0004 | 16.21 | 9500 | 0.3615 | 28.1834 |
| 0.0001 | 17.06 | 10000 | 0.3410 | 26.7402 |
| 0.0002 | 17.92 | 10500 | 0.3327 | 28.1834 |
| 0.0001 | 18.77 | 11000 | 0.3314 | 28.6078 |
| 0.0001 | 19.62 | 11500 | 0.3315 | 28.3531 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.13.3