metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: pogny_10_32_0.01
results: []
pogny_10_32_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: 1.6859
- 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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|
| 2.8512 | 1.0 | 2409 | 3.1877 | 0.4376 | 0.2665 |
| 2.7295 | 2.0 | 4818 | 3.5982 | 0.0702 | 0.0092 |
| 2.5873 | 3.0 | 7227 | 1.9106 | 0.4376 | 0.2665 |
| 2.3248 | 4.0 | 9636 | 2.4274 | 0.4376 | 0.2665 |
| 2.2087 | 5.0 | 12045 | 2.0673 | 0.2545 | 0.1032 |
| 2.17 | 6.0 | 14454 | 2.3342 | 0.4376 | 0.2665 |
| 2.0611 | 7.0 | 16863 | 1.9937 | 0.4376 | 0.2665 |
| 1.8834 | 8.0 | 19272 | 1.8107 | 0.4376 | 0.2665 |
| 1.7959 | 9.0 | 21681 | 1.7571 | 0.4376 | 0.2665 |
| 1.7009 | 10.0 | 24090 | 1.6859 | 0.4376 | 0.2665 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2
- Datasets 2.19.1
- Tokenizers 0.19.1