---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0605
- F1: 0.9264
- Roc Auc: 0.9583
- Accuracy: 0.9364

## 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: 0.003
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 289  | 0.1752          | 0.7926 | 0.8617  | 0.8295   |
| 0.1506        | 2.0   | 578  | 0.0964          | 0.8924 | 0.9262  | 0.9102   |
| 0.1506        | 3.0   | 867  | 0.0782          | 0.9116 | 0.9517  | 0.9233   |
| 0.0518        | 4.0   | 1156 | 0.0695          | 0.9132 | 0.9309  | 0.9284   |
| 0.0518        | 5.0   | 1445 | 0.0626          | 0.9320 | 0.9628  | 0.9395   |
| 0.0284        | 6.0   | 1734 | 0.0595          | 0.9270 | 0.9621  | 0.9364   |
| 0.0109        | 7.0   | 2023 | 0.0605          | 0.9264 | 0.9583  | 0.9364   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2