---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-domains
  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. -->

# roberta-finetuned-domains

This model is a fine-tuned version of [roberta-base](https://huggingface.co./roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5388
- F1: 0.2879
- Roc Auc: 0.5757
- Accuracy: 0.2533

## 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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 768
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.3789        | 0.97  | 31   | 0.4545          | 0.0004 | 0.4997  | 0.0002   |
| 0.2729        | 1.97  | 63   | 0.4684          | 0.2193 | 0.5479  | 0.1668   |
| 0.1905        | 2.98  | 95   | 0.5180          | 0.2491 | 0.5566  | 0.2100   |
| 0.1568        | 3.98  | 127  | 0.5263          | 0.2633 | 0.5636  | 0.2236   |
| 0.1398        | 4.98  | 159  | 0.5298          | 0.2862 | 0.5751  | 0.2492   |
| 0.131         | 5.83  | 186  | 0.5388          | 0.2879 | 0.5757  | 0.2533   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3