---
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