|
--- |
|
license: mit |
|
base_model: roberta-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: RewardModel_RobertaBase |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# RewardModel_RobertaBase |
|
|
|
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1047 |
|
- F1: 0.9722 |
|
- Roc Auc: 0.9792 |
|
- Accuracy: 0.9722 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- 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 | F1 | Roc Auc | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
|
| No log | 1.0 | 15 | 0.6256 | 0.0 | 0.5 | 0.0 | |
|
| No log | 2.0 | 30 | 0.5210 | 0.3448 | 0.6042 | 0.2083 | |
|
| No log | 3.0 | 45 | 0.3479 | 0.8143 | 0.8576 | 0.7639 | |
|
| No log | 4.0 | 60 | 0.2431 | 0.9241 | 0.9444 | 0.9167 | |
|
| No log | 5.0 | 75 | 0.1917 | 0.9315 | 0.9514 | 0.9167 | |
|
| No log | 6.0 | 90 | 0.1364 | 0.9655 | 0.9757 | 0.9583 | |
|
| 0.3628 | 7.0 | 105 | 0.1120 | 0.9583 | 0.9688 | 0.9583 | |
|
| 0.3628 | 8.0 | 120 | 0.0967 | 0.9655 | 0.9757 | 0.9583 | |
|
| 0.3628 | 9.0 | 135 | 0.1047 | 0.9722 | 0.9792 | 0.9722 | |
|
| 0.3628 | 10.0 | 150 | 0.0928 | 0.9722 | 0.9792 | 0.9722 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
