|
|
--- |
|
|
library_name: transformers |
|
|
|
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: roberta-mlm-model-v1 |
|
|
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. --> |
|
|
|
|
|
# roberta-mlm-model-v1 |
|
|
|
|
|
This model is a fine-tuned version of [roberta-mlm-model-v1/checkpoint-60000](https://huggingface.co//home/uet/DucDo/GHTK/roberta-mlm-model-v1/checkpoint-60000) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: nan |
|
|
|
|
|
## 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: 0.0005 |
|
|
- train_batch_size: 32 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 1000 |
|
|
- num_epochs: 4 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:------:|:---------------:| |
|
|
| 0.0 | 0.1242 | 5000 | nan | |
|
|
| 0.0 | 0.2483 | 10000 | nan | |
|
|
| 0.0 | 0.3725 | 15000 | nan | |
|
|
| 0.0 | 0.4966 | 20000 | nan | |
|
|
| 0.0 | 0.6208 | 25000 | nan | |
|
|
| 0.0 | 0.7449 | 30000 | nan | |
|
|
| 0.0 | 0.8691 | 35000 | nan | |
|
|
| 0.0 | 0.9932 | 40000 | nan | |
|
|
| 0.0 | 1.1174 | 45000 | nan | |
|
|
| 0.0 | 1.2416 | 50000 | nan | |
|
|
| 0.0 | 1.3657 | 55000 | nan | |
|
|
| 0.0 | 1.4899 | 60000 | nan | |
|
|
| 0.0 | 1.6140 | 65000 | nan | |
|
|
| 0.0 | 1.7382 | 70000 | nan | |
|
|
| 0.0 | 1.8623 | 75000 | nan | |
|
|
| 0.0 | 1.9865 | 80000 | nan | |
|
|
| 0.0 | 2.1106 | 85000 | nan | |
|
|
| 0.0 | 2.2348 | 90000 | nan | |
|
|
| 0.0 | 2.3590 | 95000 | nan | |
|
|
| 0.0 | 2.4831 | 100000 | nan | |
|
|
| 0.0 | 2.6073 | 105000 | nan | |
|
|
| 0.0 | 2.7314 | 110000 | nan | |
|
|
| 0.0 | 2.8556 | 115000 | nan | |
|
|
| 0.0 | 2.9797 | 120000 | nan | |
|
|
| 0.0 | 3.1039 | 125000 | nan | |
|
|
| 0.0 | 3.2280 | 130000 | nan | |
|
|
| 0.0 | 3.3522 | 135000 | nan | |
|
|
| 0.0 | 3.4764 | 140000 | nan | |
|
|
| 0.0 | 3.6005 | 145000 | nan | |
|
|
| 0.0 | 3.7247 | 150000 | nan | |
|
|
| 0.0 | 3.8488 | 155000 | nan | |
|
|
| 0.0 | 3.9730 | 160000 | nan | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.50.0 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.4.1 |
|
|
- Tokenizers 0.21.1 |
|
|
|
