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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: ModernBERT-base-ft-fineweb-edu-annotations
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. -->
# ModernBERT-base-ft-fineweb-edu-annotations
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: 0.8522
- F1 Score: 0.6669
- Precision Score: 0.6888
- Recall Score: 0.652
## 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: 8e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score | Precision Score | Recall Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|
| 1.1843 | 1.0 | 32 | 0.8882 | 0.6753 | 0.7256 | 0.639 |
| 0.793 | 2.0 | 64 | 0.8479 | 0.6875 | 0.7819 | 0.64 |
| 0.5971 | 3.0 | 96 | 0.8522 | 0.6669 | 0.6888 | 0.652 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0