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---
base_model: klue/roberta-small
tags:
- generated_from_trainer
model-index:
- name: my_model
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. -->
# my_model
This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4546
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.5259 | 1.0 | 4820 | 1.3120 |
| 1.2116 | 2.0 | 9640 | 1.0790 |
| 1.0629 | 3.0 | 14460 | 0.9467 |
| 0.9722 | 4.0 | 19280 | 0.8650 |
| 0.912 | 5.0 | 24100 | 0.8258 |
| 0.8514 | 6.0 | 28920 | 0.7731 |
| 0.8308 | 7.0 | 33740 | 0.7558 |
| 0.7854 | 8.0 | 38560 | 0.7081 |
| 0.74 | 9.0 | 43380 | 0.6947 |
| 0.738 | 10.0 | 48200 | 0.6608 |
| 0.7335 | 11.0 | 53020 | 0.6485 |
| 0.675 | 12.0 | 57840 | 0.6354 |
| 0.6655 | 13.0 | 62660 | 0.6106 |
| 0.6458 | 14.0 | 67480 | 0.6029 |
| 0.6256 | 15.0 | 72300 | 0.5821 |
| 0.6191 | 16.0 | 77120 | 0.5737 |
| 0.5979 | 17.0 | 81940 | 0.5696 |
| 0.6 | 18.0 | 86760 | 0.5595 |
| 0.5812 | 19.0 | 91580 | 0.5317 |
| 0.5736 | 20.0 | 96400 | 0.5282 |
| 0.5597 | 21.0 | 101220 | 0.5407 |
| 0.5665 | 22.0 | 106040 | 0.5404 |
| 0.5546 | 23.0 | 110860 | 0.5320 |
| 0.5574 | 24.0 | 115680 | 0.5160 |
| 0.5346 | 25.0 | 120500 | 0.5220 |
| 0.5323 | 26.0 | 125320 | 0.5099 |
| 0.5251 | 27.0 | 130140 | 0.4943 |
| 0.5254 | 28.0 | 134960 | 0.4907 |
| 0.5154 | 29.0 | 139780 | 0.4761 |
| 0.4914 | 30.0 | 144600 | 0.4958 |
| 0.5085 | 31.0 | 149420 | 0.4595 |
| 0.4897 | 32.0 | 154240 | 0.4697 |
| 0.4868 | 33.0 | 159060 | 0.4664 |
| 0.4779 | 34.0 | 163880 | 0.4684 |
| 0.4732 | 35.0 | 168700 | 0.4781 |
| 0.4757 | 36.0 | 173520 | 0.4687 |
| 0.4702 | 37.0 | 178340 | 0.4484 |
| 0.4652 | 38.0 | 183160 | 0.4522 |
| 0.4522 | 39.0 | 187980 | 0.4622 |
| 0.4559 | 40.0 | 192800 | 0.4546 |
| 0.4558 | 41.0 | 197620 | 0.4370 |
| 0.4482 | 42.0 | 202440 | 0.4359 |
| 0.4451 | 43.0 | 207260 | 0.4467 |
| 0.4383 | 44.0 | 212080 | 0.4401 |
| 0.4489 | 45.0 | 216900 | 0.4309 |
| 0.4347 | 46.0 | 221720 | 0.4256 |
| 0.4356 | 47.0 | 226540 | 0.4423 |
| 0.4447 | 48.0 | 231360 | 0.4441 |
| 0.4324 | 49.0 | 236180 | 0.4405 |
| 0.4278 | 50.0 | 241000 | 0.4306 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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