metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
datasets:
- klue
model-index:
- name: sts_klue_roberta_large_ep7_ckpt
results: []
sts_klue_roberta_large_ep7_ckpt
This model is a fine-tuned version of klue/roberta-large on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3504
- Mse: 0.3504
- Mae: 0.4341
- R2: 0.8395
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 |
|---|---|---|---|---|---|---|
| 1.3054 | 1.0 | 183 | 0.4871 | 0.4871 | 0.5352 | 0.7769 |
| 0.1813 | 2.0 | 366 | 0.3509 | 0.3509 | 0.4634 | 0.8393 |
| 0.1282 | 3.0 | 549 | 0.3518 | 0.3518 | 0.4562 | 0.8389 |
| 0.0893 | 4.0 | 732 | 0.3658 | 0.3658 | 0.4426 | 0.8325 |
| 0.0641 | 5.0 | 915 | 0.3790 | 0.3790 | 0.4551 | 0.8264 |
| 0.0424 | 6.0 | 1098 | 0.3836 | 0.3836 | 0.4591 | 0.8243 |
| 0.0297 | 7.0 | 1281 | 0.3504 | 0.3504 | 0.4341 | 0.8395 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3