metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
datasets:
- klue
model-index:
- name: sts_klue_roberta_large_ep9
results: []
sts_klue_roberta_large_ep9
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: 0.3567
- Mse: 0.3567
- Mae: 0.4407
- R2: 0.8367
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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 |
|---|---|---|---|---|---|---|
| 1.3093 | 1.0 | 183 | 0.4915 | 0.4915 | 0.5401 | 0.7750 |
| 0.2188 | 2.0 | 366 | 0.4399 | 0.4399 | 0.4982 | 0.7986 |
| 0.1327 | 3.0 | 549 | 0.4022 | 0.4022 | 0.4647 | 0.8158 |
| 0.1043 | 4.0 | 732 | 0.4094 | 0.4094 | 0.4680 | 0.8125 |
| 0.074 | 5.0 | 915 | 0.4218 | 0.4218 | 0.4784 | 0.8069 |
| 0.0552 | 6.0 | 1098 | 0.3424 | 0.3424 | 0.4356 | 0.8432 |
| 0.0394 | 7.0 | 1281 | 0.3925 | 0.3925 | 0.4691 | 0.8203 |
| 0.031 | 8.0 | 1464 | 0.3723 | 0.3723 | 0.4510 | 0.8295 |
| 0.0234 | 9.0 | 1647 | 0.3567 | 0.3567 | 0.4407 | 0.8367 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3