| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: modernbert_seeker |
| 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_seeker |
| |
| 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: 1.8876 |
| - F1: 0.7635 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use 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: 25 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | No log | 1.0 | 92 | 0.6179 | 0.5993 | |
| | 0.7932 | 2.0 | 184 | 0.6113 | 0.5993 | |
| | 0.6589 | 3.0 | 276 | 0.6632 | 0.6305 | |
| | 0.6418 | 4.0 | 368 | 0.6268 | 0.5993 | |
| | 0.6315 | 5.0 | 460 | 0.9375 | 0.2508 | |
| | 0.6522 | 6.0 | 552 | 0.5820 | 0.5886 | |
| | 0.6183 | 7.0 | 644 | 0.5538 | 0.6857 | |
| | 0.6136 | 8.0 | 736 | 0.5223 | 0.6736 | |
| | 0.496 | 9.0 | 828 | 0.7308 | 0.7777 | |
| | 0.4858 | 10.0 | 920 | 0.7452 | 0.7832 | |
| | 0.4181 | 11.0 | 1012 | 0.7523 | 0.7799 | |
| | 0.3395 | 12.0 | 1104 | 1.1841 | 0.7417 | |
| | 0.3395 | 13.0 | 1196 | 0.7770 | 0.8181 | |
| | 0.2375 | 14.0 | 1288 | 1.1497 | 0.7773 | |
| | 0.1728 | 15.0 | 1380 | 1.5189 | 0.7635 | |
| | 0.0324 | 16.0 | 1472 | 1.6500 | 0.7420 | |
| | 0.0764 | 17.0 | 1564 | 1.5011 | 0.7635 | |
| | 0.0244 | 18.0 | 1656 | 1.5790 | 0.7544 | |
| | 0.0002 | 19.0 | 1748 | 1.9299 | 0.7539 | |
| | 0.0004 | 20.0 | 1840 | 1.7885 | 0.7635 | |
| | 0.0001 | 21.0 | 1932 | 1.8230 | 0.7635 | |
| | 0.0001 | 22.0 | 2024 | 1.8578 | 0.7635 | |
| | 0.0 | 23.0 | 2116 | 1.8765 | 0.7635 | |
| | 0.0 | 24.0 | 2208 | 1.8845 | 0.7635 | |
| | 0.0 | 25.0 | 2300 | 1.8876 | 0.7635 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.48.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
| |
