| --- |
| library_name: transformers |
| language: |
| - en |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: DisamBertSingleSense-base |
| 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. --> |
|
|
| # DisamBertSingleSense-base |
|
|
| This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the semcor dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 79.1326 |
| - Precision: 0.5602 |
| - Recall: 0.5916 |
| - F1: 0.5755 |
| - Matthews: 0.5910 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: inverse_sqrt |
| - lr_scheduler_warmup_steps: 1000 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Matthews | |
| |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 0 | 0 | 614.2778 | 0.4290 | 0.3663 | 0.3952 | 0.3654 | |
| | 0.9441 | 1.0 | 28027 | 1.9705 | 0.5491 | 0.5863 | 0.5671 | 0.5858 | |
| | 0.9829 | 2.0 | 56054 | 2.1196 | 0.5651 | 0.6021 | 0.5830 | 0.6015 | |
| | 0.9407 | 3.0 | 84081 | 41.6424 | 0.5563 | 0.5938 | 0.5744 | 0.5932 | |
| | 0.8930 | 4.0 | 112108 | 666.7456 | 0.4864 | 0.5223 | 0.5037 | 0.5221 | |
| | 0.8190 | 5.0 | 140135 | 79.1326 | 0.5602 | 0.5916 | 0.5755 | 0.5910 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
| |
