---
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-new
  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-new

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: 0.3023
- F1: 0.6800
- Roc Auc: 0.7986
- Accuracy: 0.5811

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2592        | 1.0   | 1936  | 0.2815          | 0.6505 | 0.7740  | 0.5556   |
| 0.2839        | 2.0   | 3872  | 0.2787          | 0.6510 | 0.7688  | 0.5700   |
| 0.1879        | 3.0   | 5808  | 0.3023          | 0.6800 | 0.7986  | 0.5811   |
| 0.1552        | 4.0   | 7744  | 0.3485          | 0.6573 | 0.7867  | 0.5548   |
| 0.1182        | 5.0   | 9680  | 0.4063          | 0.6497 | 0.7833  | 0.5465   |
| 0.0822        | 6.0   | 11616 | 0.4614          | 0.6510 | 0.7747  | 0.5654   |


### Framework versions

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