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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: featured-articles
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. -->
# featured-articles
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9620
- Weighted F1: 0.6740
- Accepted Precision: 0.7453
- Accepted Recall: 0.7790
- Accepted F1: 0.7618
- Rejected Precision: 0.5273
- Rejected Recall: 0.4807
- Rejected F1: 0.5029
- Accuracy: 0.6779
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Weighted F1 | Accepted Precision | Accepted Recall | Accepted F1 | Rejected Precision | Rejected Recall | Rejected F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:--------:|
| 0.6595 | 1.0 | 267 | 0.6187 | 0.6876 | 0.752 | 0.7989 | 0.7747 | 0.5535 | 0.4862 | 0.5176 | 0.6929 |
| 0.4807 | 2.0 | 534 | 0.7625 | 0.5677 | 0.8030 | 0.4504 | 0.5771 | 0.4226 | 0.7845 | 0.5493 | 0.5637 |
| 0.3013 | 3.0 | 801 | 1.7444 | 0.6577 | 0.7105 | 0.9178 | 0.8010 | 0.6282 | 0.2707 | 0.3784 | 0.6985 |
| 0.0381 | 4.0 | 1068 | 1.9620 | 0.6740 | 0.7453 | 0.7790 | 0.7618 | 0.5273 | 0.4807 | 0.5029 | 0.6779 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.21.0
|