metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: RewardModelSmallerQuestionWithTwoLabelsLengthJustified
results: []
RewardModelSmallerQuestionWithTwoLabelsLengthJustified
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4883
- F1: 0.7873
- Roc Auc: 0.7877
- Accuracy: 0.7857
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.6771 | 1.0 | 185 | 0.6633 | 0.5913 | 0.5913 | 0.5913 |
| 0.6024 | 2.0 | 370 | 0.5766 | 0.7276 | 0.7282 | 0.7262 |
| 0.5358 | 3.0 | 555 | 0.4883 | 0.7873 | 0.7877 | 0.7857 |
| 0.4456 | 4.0 | 740 | 0.5200 | 0.7778 | 0.7778 | 0.7738 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0