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# RewardModelSmallerQuestionWithTwoLabelsLengthJustified

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: 0.4883
- 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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "roberta-base", "model-index": [{"name": "RewardModelSmallerQuestionWithTwoLabelsLengthJustified", "results": []}]}
transformers tensorboard safetensors roberta text-classification generated_from_trainer base_model:roberta-base license:mit autotrain_compatible endpoints_compatible has_space region:us