---
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: test_model
  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. -->

# test_model

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: 0.1449
- F1: 0.0
- Roc Auc: 0.5
- Accuracy: 0.8976

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1  | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---:|:-------:|:--------:|
| 0.1509        | 1.0   | 3491  | 0.1449          | 0.0 | 0.5     | 0.8976   |
| 0.1472        | 2.0   | 6982  | 0.1478          | 0.0 | 0.5     | 0.8976   |
| 0.1454        | 3.0   | 10473 | 0.1532          | 0.0 | 0.5     | 0.8976   |
| 0.144         | 4.0   | 13964 | 0.1457          | 0.0 | 0.5     | 0.8976   |
| 0.1463        | 5.0   | 17455 | 0.1441          | 0.0 | 0.5     | 0.8976   |
| 0.1427        | 6.0   | 20946 | 0.1463          | 0.0 | 0.5     | 0.8976   |
| 0.1423        | 7.0   | 24437 | 0.1419          | 0.0 | 0.5     | 0.8976   |
| 0.143         | 8.0   | 27928 | 0.1428          | 0.0 | 0.5     | 0.8976   |
| 0.1417        | 9.0   | 31419 | 0.1434          | 0.0 | 0.5     | 0.8976   |
| 0.1485        | 10.0  | 34910 | 0.1443          | 0.0 | 0.5     | 0.8976   |
| 0.142         | 11.0  | 38401 | 0.1455          | 0.0 | 0.5     | 0.8976   |
| 0.1402        | 12.0  | 41892 | 0.1464          | 0.0 | 0.5     | 0.8976   |
| 0.1417        | 13.0  | 45383 | 0.1423          | 0.0 | 0.5     | 0.8976   |
| 0.1452        | 14.0  | 48874 | 0.1450          | 0.0 | 0.5     | 0.8976   |
| 0.1455        | 15.0  | 52365 | 0.1423          | 0.0 | 0.5     | 0.8976   |
| 0.1355        | 16.0  | 55856 | 0.1422          | 0.0 | 0.5     | 0.8976   |
| 0.1369        | 17.0  | 59347 | 0.1431          | 0.0 | 0.5     | 0.8976   |
| 0.1416        | 18.0  | 62838 | 0.1436          | 0.0 | 0.5     | 0.8976   |
| 0.1387        | 19.0  | 66329 | 0.1418          | 0.0 | 0.5     | 0.8976   |
| 0.143         | 20.0  | 69820 | 0.1416          | 0.0 | 0.5     | 0.8976   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3