|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-tiny |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: torgo_tiny_finetune_M04_frozen_encoder |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# torgo_tiny_finetune_M04_frozen_encoder |
|
|
|
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2842 |
|
- Wer: 39.5586 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
|
| 0.7695 | 0.84 | 500 | 0.2502 | 52.2920 | |
|
| 0.0895 | 1.69 | 1000 | 0.2592 | 39.9830 | |
|
| 0.069 | 2.53 | 1500 | 0.2494 | 22.3260 | |
|
| 0.0465 | 3.37 | 2000 | 0.2667 | 29.6265 | |
|
| 0.0311 | 4.22 | 2500 | 0.2489 | 20.4584 | |
|
| 0.0241 | 5.06 | 3000 | 0.2731 | 23.1749 | |
|
| 0.0156 | 5.9 | 3500 | 0.2608 | 30.3056 | |
|
| 0.0127 | 6.75 | 4000 | 0.2944 | 25.2971 | |
|
| 0.0102 | 7.59 | 4500 | 0.2818 | 25.8913 | |
|
| 0.008 | 8.43 | 5000 | 0.2610 | 25.1273 | |
|
| 0.0079 | 9.27 | 5500 | 0.2632 | 24.6180 | |
|
| 0.0054 | 10.12 | 6000 | 0.2776 | 29.4567 | |
|
| 0.0047 | 10.96 | 6500 | 0.2758 | 28.0985 | |
|
| 0.003 | 11.8 | 7000 | 0.2744 | 26.9949 | |
|
| 0.0033 | 12.65 | 7500 | 0.2875 | 22.0713 | |
|
| 0.0022 | 13.49 | 8000 | 0.2842 | 34.7199 | |
|
| 0.0019 | 14.33 | 8500 | 0.2776 | 29.7963 | |
|
| 0.0012 | 15.18 | 9000 | 0.2850 | 35.2292 | |
|
| 0.0012 | 16.02 | 9500 | 0.2770 | 28.9474 | |
|
| 0.0006 | 16.86 | 10000 | 0.2797 | 56.3667 | |
|
| 0.0006 | 17.71 | 10500 | 0.2807 | 37.0119 | |
|
| 0.0002 | 18.55 | 11000 | 0.2849 | 36.7572 | |
|
| 0.0002 | 19.39 | 11500 | 0.2842 | 39.5586 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.7 |
|
- Tokenizers 0.13.3 |
|
|
