metadata
base_model: klue/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: aha_token_v1
results: []
aha_token_v1
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: 0.0064
- F1: 1.0
- Roc Auc: 1.0
- Accuracy: 1.0
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: 2e-05
- 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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 26 | 0.0795 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 52 | 0.0262 | 1.0 | 1.0 | 1.0 |
| No log | 3.0 | 78 | 0.0139 | 1.0 | 1.0 | 1.0 |
| No log | 4.0 | 104 | 0.0103 | 1.0 | 1.0 | 1.0 |
| No log | 5.0 | 130 | 0.0084 | 1.0 | 1.0 | 1.0 |
| No log | 6.0 | 156 | 0.0072 | 1.0 | 1.0 | 1.0 |
| No log | 7.0 | 182 | 0.0066 | 1.0 | 1.0 | 1.0 |
| No log | 8.0 | 208 | 0.0064 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1