metadata
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: cosmetic3_roberta
results: []
cosmetic3_roberta
This model is a fine-tuned version of klue/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3549
- Accuracy: 0.8520
- F1: 0.8563
- Precision: 0.8640
- Recall: 0.8526
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4186 | 1.0 | 277 | 0.2708 | 0.8877 | 0.8911 | 0.8933 | 0.8897 |
| 0.3237 | 2.0 | 554 | 0.4175 | 0.8623 | 0.8624 | 0.8755 | 0.8727 |
| 0.2054 | 3.0 | 831 | 0.4479 | 0.8986 | 0.9008 | 0.9087 | 0.9055 |
| 0.3151 | 4.0 | 1108 | 0.3885 | 0.9130 | 0.9154 | 0.9163 | 0.9173 |
| 0.1832 | 5.0 | 1385 | 0.4418 | 0.9094 | 0.9120 | 0.9122 | 0.9132 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2