---
library_name: transformers
license: mit
base_model: microsoft/deberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-deberta-base-finetuned-semeval-NT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CS221-deberta-base-finetuned-semeval-NT

This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5533
- F1: 0.7588
- Roc Auc: 0.8183
- Accuracy: 0.4693

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4331        | 1.0   | 277  | 0.3934          | 0.7185 | 0.7878  | 0.3845   |
| 0.3183        | 2.0   | 554  | 0.3692          | 0.7383 | 0.8014  | 0.4458   |
| 0.1905        | 3.0   | 831  | 0.4011          | 0.7447 | 0.8045  | 0.4819   |
| 0.1716        | 4.0   | 1108 | 0.4457          | 0.7489 | 0.8106  | 0.4531   |
| 0.0954        | 5.0   | 1385 | 0.4980          | 0.7573 | 0.8190  | 0.4567   |
| 0.075         | 6.0   | 1662 | 0.5533          | 0.7588 | 0.8183  | 0.4693   |
| 0.0442        | 7.0   | 1939 | 0.6536          | 0.7360 | 0.7985  | 0.4531   |
| 0.0075        | 8.0   | 2216 | 0.6831          | 0.7539 | 0.8135  | 0.4675   |
| 0.0111        | 9.0   | 2493 | 0.7289          | 0.7529 | 0.8124  | 0.4693   |


### Framework versions

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