metadata
base_model: klue/roberta-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: binary_every_exp
results: []
binary_every_exp
This model is a fine-tuned version of klue/roberta-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1049
- Precision: 0.9615
- Recall: 1.0
- F1: 0.9804
- Accuracy: 0.9833
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 18 | 0.1487 | 0.9583 | 0.92 | 0.9388 | 0.95 |
| No log | 2.0 | 36 | 0.1680 | 0.9583 | 0.92 | 0.9388 | 0.95 |
| No log | 3.0 | 54 | 0.1049 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
| No log | 4.0 | 72 | 0.1135 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
| No log | 5.0 | 90 | 0.1190 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
| No log | 6.0 | 108 | 0.1220 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
| No log | 7.0 | 126 | 0.1235 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
| No log | 8.0 | 144 | 0.1240 | 0.9615 | 1.0 | 0.9804 | 0.9833 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1