|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Model_G_P |
|
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. --> |
|
|
|
# Model_G_P |
|
|
|
This model was trained from scratch on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4719 |
|
- Wer: 0.5613 |
|
- Cer: 0.2386 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 30 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 0.447 | 4.17 | 400 | 2.1407 | 0.6004 | 0.2516 | |
|
| 0.4338 | 8.33 | 800 | 2.1920 | 0.6033 | 0.2505 | |
|
| 0.3209 | 12.5 | 1200 | 2.2978 | 0.6089 | 0.2601 | |
|
| 0.2327 | 16.67 | 1600 | 2.3510 | 0.5871 | 0.2459 | |
|
| 0.1735 | 20.83 | 2000 | 2.3828 | 0.5890 | 0.2480 | |
|
| 0.1344 | 25.0 | 2400 | 2.3782 | 0.5647 | 0.2399 | |
|
| 0.0909 | 29.17 | 2800 | 2.4719 | 0.5613 | 0.2386 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.13.3 |
|
|
