| | --- |
| | base_model: klue/roberta-large |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: IE_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. --> |
| |
|
| | # IE_model |
| | |
| | This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4341 |
| | - Accuracy: 0.9007 |
| | |
| | ## 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: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.9432 | 1.0 | 574 | 0.5054 | 0.8537 | |
| | | 0.4765 | 2.0 | 1148 | 0.4133 | 0.8589 | |
| | | 0.4471 | 3.0 | 1722 | 0.4228 | 0.8693 | |
| | | 0.3666 | 4.0 | 2296 | 0.4627 | 0.8815 | |
| | | 0.3508 | 5.0 | 2870 | 0.3704 | 0.8833 | |
| | | 0.325 | 6.0 | 3444 | 0.3704 | 0.9024 | |
| | | 0.2662 | 7.0 | 4018 | 0.3733 | 0.9024 | |
| | | 0.226 | 8.0 | 4592 | 0.4024 | 0.8972 | |
| | | 0.1978 | 9.0 | 5166 | 0.4198 | 0.9042 | |
| | | 0.186 | 10.0 | 5740 | 0.4341 | 0.9007 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.39.3 |
| | - Pytorch 2.2.2+cu121 |
| | - Datasets 2.19.0 |
| | - Tokenizers 0.15.2 |
| | |
