---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base-clickbait-task1-20-epoch-post_title
  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. -->

# deberta-v3-base-clickbait-task1-20-epoch-post_title

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4262
- Accuracy: 0.7275

## 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: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 200  | 0.7682          | 0.715    |
| No log        | 2.0   | 400  | 0.7289          | 0.7125   |
| 0.7821        | 3.0   | 600  | 0.7968          | 0.705    |
| 0.7821        | 4.0   | 800  | 0.9608          | 0.73     |
| 0.3436        | 5.0   | 1000 | 1.0204          | 0.7275   |
| 0.3436        | 6.0   | 1200 | 1.3033          | 0.71     |
| 0.3436        | 7.0   | 1400 | 1.4924          | 0.7325   |
| 0.1188        | 8.0   | 1600 | 1.6538          | 0.7325   |
| 0.1188        | 9.0   | 1800 | 2.1675          | 0.7      |
| 0.0458        | 10.0  | 2000 | 2.0062          | 0.71     |
| 0.0458        | 11.0  | 2200 | 2.1166          | 0.7      |
| 0.0458        | 12.0  | 2400 | 2.3641          | 0.71     |
| 0.0147        | 13.0  | 2600 | 2.3338          | 0.7      |
| 0.0147        | 14.0  | 2800 | 2.2134          | 0.7125   |
| 0.0106        | 15.0  | 3000 | 2.3733          | 0.72     |
| 0.0106        | 16.0  | 3200 | 2.3268          | 0.7175   |
| 0.0106        | 17.0  | 3400 | 2.3951          | 0.7125   |
| 0.0041        | 18.0  | 3600 | 2.4211          | 0.7275   |
| 0.0041        | 19.0  | 3800 | 2.4168          | 0.725    |
| 0.0046        | 20.0  | 4000 | 2.4262          | 0.7275   |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1