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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-8k
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-8k
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: 1.1265
- F1 Score: 0.7508
- Precision Score: 0.7556
- Recall Score: 0.7485
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------------:|:------------:|
| 0.6615 | 1.0 | 6374 | 0.5893 | 0.7574 | 0.7746 | 0.7510 |
| 0.4344 | 2.0 | 12748 | 0.6108 | 0.7600 | 0.7644 | 0.7572 |
| 0.149 | 3.0 | 19122 | 1.1265 | 0.7508 | 0.7556 | 0.7485 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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