---
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: 0.1597
- F1: 0.0
- Roc Auc: 0.5
- Accuracy: 0.8917

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1  | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
| No log        | 1.0   | 35   | 0.1597          | 0.0 | 0.5     | 0.8917   |
| No log        | 2.0   | 70   | 0.1509          | 0.0 | 0.5     | 0.8917   |
| No log        | 3.0   | 105  | 0.1507          | 0.0 | 0.5     | 0.8917   |
| No log        | 4.0   | 140  | 0.1506          | 0.0 | 0.5     | 0.8917   |
| No log        | 5.0   | 175  | 0.1503          | 0.0 | 0.5     | 0.8917   |


### Framework versions

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