---
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