---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-roberta-base-finetuned-semeval-NT
  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. -->

# CS221-roberta-base-finetuned-semeval-NT

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5269
- F1: 0.7240
- Roc Auc: 0.7938
- Accuracy: 0.4639

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4269        | 1.0   | 277  | 0.3920          | 0.6532 | 0.7374  | 0.4025   |
| 0.3157        | 2.0   | 554  | 0.3683          | 0.6965 | 0.7692  | 0.4152   |
| 0.2287        | 3.0   | 831  | 0.3818          | 0.6849 | 0.7667  | 0.4314   |
| 0.1779        | 4.0   | 1108 | 0.4116          | 0.6927 | 0.7689  | 0.4097   |
| 0.1274        | 5.0   | 1385 | 0.4471          | 0.6991 | 0.7729  | 0.4314   |
| 0.1036        | 6.0   | 1662 | 0.4658          | 0.7166 | 0.7848  | 0.4549   |
| 0.0684        | 7.0   | 1939 | 0.5065          | 0.7133 | 0.7840  | 0.4422   |
| 0.055         | 8.0   | 2216 | 0.5269          | 0.7240 | 0.7938  | 0.4639   |
| 0.0156        | 9.0   | 2493 | 0.5896          | 0.7157 | 0.7920  | 0.4513   |
| 0.0173        | 10.0  | 2770 | 0.6118          | 0.7215 | 0.7868  | 0.4477   |
| 0.0171        | 11.0  | 3047 | 0.6322          | 0.7234 | 0.7941  | 0.4513   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0