---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-large-finetuned-augmentation-LUNAR-TAPT-macro
  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-large-finetuned-augmentation-LUNAR-TAPT-macro

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2832
- F1: 0.8635
- Roc Auc: 0.8937
- Accuracy: 0.7150

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.2744        | 1.0   | 421  | 0.2710          | 0.7932 | 0.8326  | 0.5754   |
| 0.2287        | 2.0   | 842  | 0.2281          | 0.8454 | 0.8815  | 0.6758   |
| 0.1678        | 3.0   | 1263 | 0.2293          | 0.8563 | 0.8879  | 0.7049   |
| 0.1287        | 4.0   | 1684 | 0.2491          | 0.8619 | 0.8918  | 0.7126   |
| 0.1298        | 5.0   | 2105 | 0.2591          | 0.8633 | 0.8936  | 0.7173   |
| 0.0788        | 6.0   | 2526 | 0.2703          | 0.8612 | 0.8914  | 0.7138   |
| 0.0883        | 7.0   | 2947 | 0.2679          | 0.8605 | 0.8905  | 0.7203   |
| 0.0821        | 8.0   | 3368 | 0.2832          | 0.8635 | 0.8937  | 0.7150   |
| 0.0739        | 9.0   | 3789 | 0.2998          | 0.8601 | 0.8963  | 0.7156   |
| 0.0538        | 10.0  | 4210 | 0.2951          | 0.8615 | 0.8957  | 0.7167   |
| 0.0466        | 11.0  | 4631 | 0.2999          | 0.8626 | 0.8976  | 0.7126   |
| 0.0657        | 12.0  | 5052 | 0.3060          | 0.8608 | 0.8976  | 0.7203   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0