|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: Model_G_S_P_Wav2Vec2 |
|
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_S_P_Wav2Vec2 |
|
|
|
This model was trained from scratch on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.5098 |
|
- Wer: 0.5366 |
|
- Cer: 0.2277 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 1.0449 | 3.49 | 400 | 1.7576 | 0.6270 | 0.2607 | |
|
| 0.484 | 6.99 | 800 | 1.8072 | 0.6043 | 0.2536 | |
|
| 0.3335 | 10.48 | 1200 | 2.0222 | 0.5892 | 0.2500 | |
|
| 0.2559 | 13.97 | 1600 | 2.4174 | 0.5719 | 0.2448 | |
|
| 0.1999 | 17.47 | 2000 | 2.2888 | 0.5566 | 0.2376 | |
|
| 0.1546 | 20.96 | 2400 | 2.5271 | 0.5753 | 0.2400 | |
|
| 0.1225 | 24.45 | 2800 | 2.4489 | 0.5427 | 0.2327 | |
|
| 0.0983 | 27.95 | 3200 | 2.5098 | 0.5366 | 0.2277 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|