---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-bert-base-uncased-finetuned-semeval-NT-sun
  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-bert-base-uncased-finetuned-semeval-NT-sun

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4060
- F1: 0.6852
- Roc Auc: 0.7739
- Accuracy: 0.5135

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4264        | 1.0   | 93   | 0.4356          | 0.6154 | 0.7316  | 0.4811   |
| 0.3577        | 2.0   | 186  | 0.3867          | 0.6667 | 0.7663  | 0.4811   |
| 0.321         | 3.0   | 279  | 0.3666          | 0.6773 | 0.7702  | 0.4973   |
| 0.2953        | 4.0   | 372  | 0.3691          | 0.6698 | 0.7625  | 0.4973   |
| 0.236         | 5.0   | 465  | 0.3840          | 0.6667 | 0.7645  | 0.4757   |
| 0.2011        | 6.0   | 558  | 0.4060          | 0.6852 | 0.7739  | 0.5135   |
| 0.1135        | 7.0   | 651  | 0.4200          | 0.6711 | 0.7690  | 0.4865   |
| 0.1056        | 8.0   | 744  | 0.4691          | 0.6636 | 0.7607  | 0.4973   |
| 0.0854        | 9.0   | 837  | 0.4758          | 0.6727 | 0.7680  | 0.5027   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Tokenizers 0.21.0