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---
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
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
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: 2.4780
- Accuracy: 0.7
## 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 | 0.7377 | 0.705 |
| No log | 2.0 | 400 | 0.7807 | 0.67 |
| 0.7497 | 3.0 | 600 | 0.7980 | 0.7075 |
| 0.7497 | 4.0 | 800 | 0.9537 | 0.7125 |
| 0.3256 | 5.0 | 1000 | 1.1896 | 0.6975 |
| 0.3256 | 6.0 | 1200 | 1.2719 | 0.7125 |
| 0.3256 | 7.0 | 1400 | 1.6965 | 0.7 |
| 0.1192 | 8.0 | 1600 | 1.7920 | 0.7075 |
| 0.1192 | 9.0 | 1800 | 2.0342 | 0.695 |
| 0.0497 | 10.0 | 2000 | 2.1345 | 0.71 |
| 0.0497 | 11.0 | 2200 | 2.1191 | 0.7075 |
| 0.0497 | 12.0 | 2400 | 2.3217 | 0.705 |
| 0.0288 | 13.0 | 2600 | 2.3254 | 0.7075 |
| 0.0288 | 14.0 | 2800 | 2.3810 | 0.7 |
| 0.0147 | 15.0 | 3000 | 2.3537 | 0.71 |
| 0.0147 | 16.0 | 3200 | 2.3389 | 0.6975 |
| 0.0147 | 17.0 | 3400 | 2.4556 | 0.69 |
| 0.01 | 18.0 | 3600 | 2.4238 | 0.705 |
| 0.01 | 19.0 | 3800 | 2.4632 | 0.695 |
| 0.0066 | 20.0 | 4000 | 2.4780 | 0.7 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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