|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- tr |
|
|
license: apache-2.0 |
|
|
base_model: openai/whisper-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- wer |
|
|
model-index: |
|
|
- name: whisper-base |
|
|
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. --> |
|
|
|
|
|
# whisper-base |
|
|
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1952 |
|
|
- Wer: 10.4439 |
|
|
|
|
|
## 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: 32 |
|
|
- eval_batch_size: 16 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- training_steps: 60000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|
|:-------------:|:------:|:-----:|:---------------:|:-------:| |
|
|
| 0.2139 | 0.0833 | 5000 | 0.1884 | 16.6399 | |
|
|
| 0.1146 | 0.1667 | 10000 | 0.1447 | 13.0148 | |
|
|
| 0.0686 | 0.25 | 15000 | 0.1384 | 11.3586 | |
|
|
| 0.0427 | 0.3333 | 20000 | 0.1471 | 11.4970 | |
|
|
| 0.0274 | 0.4167 | 25000 | 0.1585 | 10.8926 | |
|
|
| 0.0195 | 0.5 | 30000 | 0.1702 | 11.3447 | |
|
|
| 0.0155 | 0.5833 | 35000 | 0.1773 | 10.6100 | |
|
|
| 0.0126 | 1.0062 | 40000 | 0.1863 | 11.4255 | |
|
|
| 0.0099 | 1.0895 | 45000 | 0.1929 | 10.6665 | |
|
|
| 0.01 | 1.1729 | 50000 | 0.1933 | 10.6665 | |
|
|
| 0.0085 | 1.2562 | 55000 | 0.1953 | 10.5224 | |
|
|
| 0.0085 | 1.3395 | 60000 | 0.1952 | 10.4439 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.45.2 |
|
|
- Pytorch 2.5.1+cu121 |
|
|
- Datasets 3.2.0 |
|
|
- Tokenizers 0.20.3 |
|
|
|
