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---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: xlm-roberta-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. -->
# xlm-roberta-base-clickbait-task1-20-epoch-post_title
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6481
- Accuracy: 0.6875
## 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 | 0.8494 | 0.6675 |
| No log | 2.0 | 400 | 0.7488 | 0.6975 |
| 0.8603 | 3.0 | 600 | 0.7566 | 0.7025 |
| 0.8603 | 4.0 | 800 | 0.8778 | 0.7075 |
| 0.5018 | 5.0 | 1000 | 0.9345 | 0.7025 |
| 0.5018 | 6.0 | 1200 | 1.1088 | 0.695 |
| 0.5018 | 7.0 | 1400 | 1.4765 | 0.69 |
| 0.2227 | 8.0 | 1600 | 1.7443 | 0.6975 |
| 0.2227 | 9.0 | 1800 | 1.7676 | 0.6875 |
| 0.1063 | 10.0 | 2000 | 2.1244 | 0.675 |
| 0.1063 | 11.0 | 2200 | 2.2377 | 0.6925 |
| 0.1063 | 12.0 | 2400 | 2.3395 | 0.685 |
| 0.05 | 13.0 | 2600 | 2.4198 | 0.6925 |
| 0.05 | 14.0 | 2800 | 2.5012 | 0.6875 |
| 0.0218 | 15.0 | 3000 | 2.6027 | 0.675 |
| 0.0218 | 16.0 | 3200 | 2.5422 | 0.6925 |
| 0.0218 | 17.0 | 3400 | 2.6134 | 0.68 |
| 0.0138 | 18.0 | 3600 | 2.5818 | 0.69 |
| 0.0138 | 19.0 | 3800 | 2.6337 | 0.6825 |
| 0.0078 | 20.0 | 4000 | 2.6481 | 0.6875 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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