metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: model_y3_research_1
results: []
model_y3_research_1
This model is a fine-tuned version of klue/roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9169
- Accuracy: 0.5979
- F1: 0.5435
- Precision: 0.5801
- Recall: 0.5487
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.9798 | 1.0 | 97 | 0.9334 | 0.5833 | 0.4128 | 0.4359 | 0.4577 |
| 0.9489 | 2.0 | 194 | 0.9621 | 0.4792 | 0.2160 | 0.1597 | 0.3333 |
| 0.9564 | 3.0 | 291 | 0.9505 | 0.5104 | 0.3456 | 0.3323 | 0.3764 |
| 0.8319 | 4.0 | 388 | 0.8693 | 0.6458 | 0.5980 | 0.5970 | 0.6167 |
| 0.7045 | 5.0 | 485 | 1.1875 | 0.5729 | 0.4888 | 0.5051 | 0.4891 |
| 0.6337 | 6.0 | 582 | 1.7888 | 0.6042 | 0.4288 | 0.4648 | 0.4752 |
| 0.3682 | 7.0 | 679 | 2.0383 | 0.5521 | 0.4904 | 0.4889 | 0.4967 |
| 0.2195 | 8.0 | 776 | 2.3023 | 0.5625 | 0.4993 | 0.4986 | 0.5055 |
| 0.0244 | 9.0 | 873 | 2.8742 | 0.5417 | 0.4650 | 0.4650 | 0.4674 |
| 0.1459 | 10.0 | 970 | 2.9738 | 0.5521 | 0.4999 | 0.5001 | 0.5157 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2