rossevine's picture
update model card README.md
4e4d143
|
raw
history blame
1.45 kB
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Model_G_S_Berita_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_Berita_Wav2Vec2
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0239
- Wer: 0.0350
- Cer: 0.0055
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.3535 | 12.5 | 400 | 0.0680 | 0.0888 | 0.0139 |
| 0.0269 | 25.0 | 800 | 0.0239 | 0.0350 | 0.0055 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 1.18.3
- Tokenizers 0.13.3