metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny_10_64_0.01
results: []
pogny_10_64_0.01
This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6851
- Accuracy: 0.4376
- F1: 0.2665
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: 0.01
- 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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.491 | 1.0 | 1205 | 2.5033 | 0.4376 | 0.2665 |
| 2.4679 | 2.0 | 2410 | 1.9460 | 0.4376 | 0.2665 |
| 2.302 | 3.0 | 3615 | 2.4098 | 0.0702 | 0.0092 |
| 2.1762 | 4.0 | 4820 | 2.2698 | 0.0545 | 0.0056 |
| 2.0639 | 5.0 | 6025 | 1.9917 | 0.4376 | 0.2665 |
| 2.0031 | 6.0 | 7230 | 1.9130 | 0.4376 | 0.2665 |
| 1.9241 | 7.0 | 8435 | 2.0131 | 0.4376 | 0.2665 |
| 1.8227 | 8.0 | 9640 | 1.8212 | 0.4376 | 0.2665 |
| 1.7854 | 9.0 | 10845 | 1.7379 | 0.4376 | 0.2665 |
| 1.7037 | 10.0 | 12050 | 1.6851 | 0.4376 | 0.2665 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1