| --- |
| 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-omsti |
| 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-omsti |
|
|
| 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: 3.1672 |
| - Precision: 0.7233 |
| - Recall: 0.7064 |
| - F1: 0.7148 |
| - Matthews: 0.7058 |
|
|
| ## 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: 64 |
| - eval_batch_size: 64 |
| - 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 | 88.3567 | 0.4162 | 0.3628 | 0.3877 | 0.3621 | |
| | 2.0504 | 1.0 | 17769 | 3.1969 | 0.7332 | 0.7147 | 0.7238 | 0.7142 | |
| | 1.8615 | 2.0 | 35538 | 3.3690 | 0.7334 | 0.7130 | 0.7230 | 0.7124 | |
| | 1.8386 | 3.0 | 53307 | 3.2408 | 0.7246 | 0.7064 | 0.7154 | 0.7058 | |
| | 1.8802 | 4.0 | 71076 | 3.2913 | 0.7337 | 0.7121 | 0.7227 | 0.7115 | |
| | 1.7798 | 5.0 | 88845 | 3.1672 | 0.7233 | 0.7064 | 0.7148 | 0.7058 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
| |
