|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: openai/whisper-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: fs-w-xavier-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. --> |
|
|
|
# fs-w-xavier-base |
|
|
|
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3748 |
|
- Wer: 97.8158 |
|
- Cer: 77.1470 |
|
|
|
## 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: 500 |
|
- training_steps: 5000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------:| |
|
| 3.6366 | 4.5872 | 500 | 3.6746 | 94.9193 | 77.2587 | |
|
| 0.843 | 9.1743 | 1000 | 1.0679 | 99.8575 | 79.0879 | |
|
| 0.388 | 13.7615 | 1500 | 0.6110 | 102.8965 | 81.0031 | |
|
| 0.3226 | 18.3486 | 2000 | 0.4898 | 104.7958 | 86.9718 | |
|
| 0.2976 | 22.9358 | 2500 | 0.4571 | 113.0579 | 88.8956 | |
|
| 0.2679 | 27.5229 | 3000 | 0.4198 | 103.5613 | 80.5050 | |
|
| 0.2327 | 32.1101 | 3500 | 0.4085 | 103.8462 | 82.1711 | |
|
| 0.2099 | 36.6972 | 4000 | 0.3883 | 101.3295 | 78.2807 | |
|
| 0.1959 | 41.2844 | 4500 | 0.3780 | 100.1425 | 77.5936 | |
|
| 0.1681 | 45.8716 | 5000 | 0.3748 | 97.8158 | 77.1470 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.1 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.0 |
|
|
