|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: openai/whisper-small |
|
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. --> |
|
|
|
# openai/whisper-small |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the pphuc25/EngMed dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0004 |
|
- Wer: 21.9876 |
|
- Cer: 17.0884 |
|
|
|
## 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: 8 |
|
- 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: 100 |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
|
| 0.7291 | 1.0 | 386 | 0.3415 | 25.0142 | 20.1560 | |
|
| 0.472 | 2.0 | 772 | 0.2196 | 27.4412 | 24.5293 | |
|
| 0.2716 | 3.0 | 1158 | 0.1239 | 31.2274 | 28.4146 | |
|
| 0.1409 | 4.0 | 1544 | 0.0740 | 38.1165 | 34.4281 | |
|
| 0.1283 | 5.0 | 1930 | 0.0465 | 40.1171 | 35.9613 | |
|
| 0.0631 | 6.0 | 2316 | 0.0310 | 36.5868 | 30.1992 | |
|
| 0.0582 | 7.0 | 2702 | 0.0177 | 32.1775 | 26.2129 | |
|
| 0.0531 | 8.0 | 3088 | 0.0131 | 31.8391 | 27.8444 | |
|
| 0.0238 | 9.0 | 3474 | 0.0091 | 24.2508 | 18.5448 | |
|
| 0.0149 | 10.0 | 3860 | 0.0060 | 24.8696 | 19.3220 | |
|
| 0.0057 | 11.0 | 4246 | 0.0050 | 26.8193 | 21.7715 | |
|
| 0.0077 | 12.0 | 4632 | 0.0031 | 23.0677 | 19.1910 | |
|
| 0.0073 | 13.0 | 5018 | 0.0028 | 24.7584 | 19.3135 | |
|
| 0.0052 | 14.0 | 5404 | 0.0014 | 25.8657 | 19.1331 | |
|
| 0.0031 | 15.0 | 5790 | 0.0009 | 21.5274 | 17.0940 | |
|
| 0.0039 | 16.0 | 6176 | 0.0007 | 22.1520 | 17.1637 | |
|
| 0.0013 | 17.0 | 6562 | 0.0006 | 22.9021 | 17.7620 | |
|
| 0.0009 | 18.0 | 6948 | 0.0005 | 21.9899 | 17.3717 | |
|
| 0.001 | 19.0 | 7334 | 0.0004 | 22.1923 | 17.4027 | |
|
| 0.0004 | 20.0 | 7720 | 0.0004 | 21.9876 | 17.0884 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.1 |
|
- Pytorch 2.3.0 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
